From fc8e67ff9b69258276a221549b67e19d366ffd8e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ezequiel=20Leonardo=20Casta=C3=B1o?=
 <14986783+ELC@users.noreply.github.com>
Date: Wed, 18 Jun 2025 23:02:41 -0300
Subject: [PATCH 1/2] Scraped pydata-eindhoven-2022
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Fixes #xxx

Event config:
~~~yaml
repo_dir: W:\Repositories\pyvideo-data

# Copy the event template here and adapt to the event parameters

# Only repo_dir: and events: are loaded

# =============================================================================
events:
  # - title: PyData Virginia 2025
  #   dir: pydata-virginia-2025
  #   youtube_list:
  #     - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qLS7Mk-jI9jhb4t5UY6yDW
  #   related_urls:
  #     - label: Conference Website
  #       url: https://pydata.org/virginia2025
  #   language: eng
  #   dates:
  #     begin: 2025-04-18
  #     end: 2025-04-19
  #     default: 2025-04-18
  #   minimal_download: false
  #   issue: xxx
  #   overwrite:
  #     # all: true # takes precedence over add_new_files and existing_files_fields
  #     add_new_files: true
  #     existing_files_fields:
  #       - duration
  #       - thumbnail_url
  #       - videos
  #       - description
  #       - language
  #       - recorded
  #       - related_urls
  #       - speakers
  #       - tags
  #       - title
  #   tags:

  # - title: PyData Global 2024
  #   dir: pydata-global-2024
  #   youtube_list:
  #     - https://www.youtube.com/playlist?list=PLGVZCDnMOq0otKlHvES9iBFtVQ71yZhed
  #   related_urls:
  #     - label: Conference Website
  #       url: https://pydata.org/global2024
  #   language: eng
  #   dates:
  #     begin: 2024-12-03
  #     end: 2024-12-05
  #     default: 2024-12-03
  #   minimal_download: false
  #   issue: xxx
  #   overwrite:
  #     # all: true # takes precedence over add_new_files and existing_files_fields
  #     add_new_files: true
  #     existing_files_fields:
  #       - duration
  #       - thumbnail_url
  #       - videos
  #       - description
  #       - language
  #       - recorded
  #       - related_urls
  #       - speakers
  #       - tags
  #       - title
  #   tags:

  - title: PyData New York City 2024
    dir: pydata-new-york-city-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0ohEIZ-_wM2W_xqSVjyA3dC
    related_urls:
      - label: Conference Website
        url: https://pydata.org/nyc2024
    language: eng
    dates:
      begin: 2024-11-06
      end: 2024-11-08
      default: 2024-11-06
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Tel Aviv 2024
    dir: pydata-tel-avid-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0pRsGPxDvLZfuufNgqREc0a
    related_urls:
      - label: Conference Website
        url: https://pydata.org/telaviv2024/
    language: eng
    dates:
      begin: 2024-11-04
      end: 2024-11-04
      default: 2024-11-04
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Paris 2024
    dir: pydata-paris-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0pKya8gksd00ennKuyoH7v7
    related_urls:
      - label: Conference Website
        url: https://pydata.org/paris2024
    language: eng
    dates:
      begin: 2024-09-25
      end: 2024-09-26
      default: 2024-09-25
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Amsterdam 2024
    dir: pydata-amsterdam-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0reU2lzNZCn9obkyRVaSnpF
    related_urls:
      - label: Conference Website
        url: https://web.archive.org/web/20240822042916/https://amsterdam.pydata.org/
    language: eng
    dates:
      begin: 2024-09-18
      end: 2024-09-20
      default: 2024-09-18
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Vermont 2024
    dir: pydata-vermont-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0pME_xSRdmoYFzhlsHJYM8I
    related_urls:
      - label: Conference Website
        url: https://pydata.org/vermont2024/
    language: eng
    dates:
      begin: 2024-07-29
      end: 2024-07-30
      default: 2024-07-29
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Eindhoven 2024
    dir: pydata-eindhoven-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0q7a2aoNP1au_1egfZEjGL6
    related_urls:
      - label: Conference Website
        url: https://pydata.org/eindhoven2024/
    language: eng
    dates:
      begin: 2024-07-11
      end: 2024-07-11
      default: 2024-07-11
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData London 2024
    dir: pydata-london-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0rrhYTNedKKuJ9716fEaAdK
    related_urls:
      - label: Conference Website
        url: https://pydata.org/london2024/
    language: eng
    dates:
      begin: 2024-06-14
      end: 2024-06-16
      default: 2024-06-14
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Berlin 2024
    dir: pydata-berlin-2024
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0r2tGyr-hjbnCrjXRkCMvwB
    related_urls:
      - label: Conference Website
        url: https://2024.pycon.de/
    language: eng
    dates:
      begin: 2024-06-14
      end: 2024-06-16
      default: 2024-06-14
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Global 2023
    dir: pydata-global-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0poULd1C4oUdPbPkTe4poJx
    related_urls:
      - label: Conference Website
        url: https://pydata.org/global2023/
    language: eng
    dates:
      begin: 2023-12-06
      end: 2023-12-08
      default: 2023-12-06
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Eindhoven 2023
    dir: pydata-eindhoven-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qkbJjIfppGO44yhDV2i4gR
    related_urls:
      - label: Conference Website
        url: https://web.archive.org/web/20240930133013/http://pydata.org/eindhoven2023
    language: eng
    dates:
      begin: 2023-11-30
      end: 2023-11-30
      default: 2023-11-30
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData New York City 2023
    dir: pydata-new-york-city-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0o79mT1hHyqtFDSNzXXSYQM
    related_urls:
      - label: Conference Website
        url: https://pydata.org/nyc2023/
    language: eng
    dates:
      begin: 2023-11-01
      end: 2023-11-03
      default: 2023-11-01
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Amsterdam 2023
    dir: pydata-amsterdam-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0pADyz2VboxPFIdrsozlENg
    related_urls:
      - label: Conference Website
        url: https://amsterdam2023.pydata.org/cfp/schedule/
    language: eng
    dates:
      begin: 2023-09-14
      end: 2023-09-16
      default: 2023-09-14
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Seattle 2023
    dir: pydata-seattle-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0q81_-rt5jzJ--ZEgcNArKb
    related_urls:
      - label: Conference Website
        url: https://pydata.org/seattle2023/
    language: eng
    dates:
      begin: 2023-04-26
      end: 2023-04-28
      default: 2023-04-26
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Berlin 2023
    dir: pydata-berlin-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0peDguAzds7kVmBr8avp46K
    related_urls:
      - label: Conference Website
        url: https://2023.pycon.de/
    language: eng
    dates:
      begin: 2023-04-17
      end: 2023-04-19
      default: 2023-04-17
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Yerevan 2023
    dir: pydata-yerevan-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0pJKftCB2BtalTDE-2xS20g
    language: eng
    dates:
      begin: 2023-10-23
      end: 2024-11-07
      default: 2023-10-23
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Trójmiasto 2023
    dir: pydata-trojmiasto-2023
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qS0mI7s9tpXnS-XV5l_Ibs
    related_urls:
      - label: Conference Website
        url: https://www.meetup.com/pl-PL/pydata-trojmiasto/
    language: eng
    dates:
      begin: 2023-10-24
      end: 2023-10-24
      default: 2023-10-24
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Tel Avid 2022
    dir: pydata-tel-avid-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0p6o_fjjdNPqy1rps49z2S0
    related_urls:
      - label: Conference Website
        url: https://pydata.org/telaviv2022/
    language: eng
    dates:
      begin: 2022-12-13
      end: 2022-12-13
      default: 2022-12-13
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Eindhoven 2022
    dir: pydata-eindhoven-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0pI60MsrFpHcII1qWm7drmZ
    related_urls:
      - label: Conference Website
        url: https://pydata.org/eindhoven2022/
    language: eng
    dates:
      begin: 2022-12-02
      end: 2022-12-02
      default: 2022-12-02
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Global 2022
    dir: pydata-global-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qgYUt0yn7F80wmzCnj2dEq
    related_urls:
      - label: Conference Website
        url: https://pydata.org/global2022/
    language: eng
    dates:
      begin: 2022-12-01
      end: 2022-12-03
      default: 2022-12-01
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData New York City 2022
    dir: pydata-new-york-city-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0opPc5-dp6ZDCFvOqDBlUuv
    related_urls:
      - label: Conference Website
        url: https://pydata.org/nyc2022/
    language: eng
    dates:
      begin: 2022-11-09
      end: 2022-11-11
      default: 2022-11-09
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Yerevan 2022
    dir: pydata-yerevan-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qWwVVDmdOw6oxAlqqH8Ca-
    related_urls:
      - label: Conference Website
        url: https://pydata.org/yerevan2022/
    language: eng
    dates:
      begin: 2022-08-12
      end: 2022-08-13
      default: 2022-08-12
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData London 2022
    dir: pydata-london-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qT0MXnci7VBSF-U-0WaQ-w
    related_urls:
      - label: Conference Website
        url: https://pydata.org/london2022/
    language: eng
    dates:
      begin: 2022-06-17
      end: 2022-06-19
      default: 2022-06-17
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Berlin 2022
    dir: pydata-berlin-2022
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0p0Fal8_YKg6fPXnf3iPtwD
    related_urls:
      - label: Conference Website
        url: https://2022.pycon.de/
    language: eng
    dates:
      begin: 2022-04-11
      end: 2022-04-13
      default: 2022-04-11
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Global 2021
    dir: pydata-global-2021
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0rHb3JXG6puQnUAclFFZMlh
    related_urls:
      - label: Conference Website
        url: https://pydata.org/global2021/
    language: eng
    dates:
      begin: 2021-10-28
      end: 2021-10-30
      default: 2021-10-28
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Eindhoven 2021
    dir: pydata-eindhoven-2021
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0rBKcoKoaWJiMrDGdNr2_S0
    related_urls:
      - label: Conference Website
        url: https://pydata.org/eindhoven2021/
    language: eng
    dates:
      begin: 2021-11-12
      end: 2021-11-12
      default: 2021-11-12
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Global 2020
    dir: pydata-global-2020
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0r0eC9BnITmYJ786p9Y1Q8D
    related_urls:
      - label: Conference Website
        url: https://pydataglobal.github.io/
    language: eng
    dates:
      begin: 2020-11-11
      end: 2020-11-15
      default: 2020-11-11
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Eindhoven 2020
    dir: pydata-eindhoven-2020
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qpKjuGgNOgtOxIuATvnqEr
    related_urls:
      - label: Conference Website
        url: https://pydata.org/eindhoven2020/schedule/
    language: eng
    dates:
      begin: 2020-10-07
      end: 2020-10-09
      default: 2020-10-07
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Amsterdam 2020
    dir: pydata-amsterdam-2020
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0oX4ymLgldSvpfiZj-S8-fH
    related_urls:
      - label: Conference Website
        url: https://datasciencedistrict.nl/pydata-festival-amsterda/
    language: eng
    dates:
      begin: 2020-06-15
      end: 2020-06-20
      default: 2020-06-15
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData South Africa 2018
    dir: pydata-south-africa-2018
    youtube_list:
      - https://www.youtube.com/watch?v=Lvw3Lp3KrTM&list=PLGjWYNrNnSuc78h5x23A5mLAzWlCl9LGf
    related_urls:
      - label: Conference Website
        url: https://2018.za.pycon.org/
    language: eng
    dates:
      begin: 2018-10-11
      end: 2018-10-12
      default: 2018-10-11
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

  - title: PyData Hamburg 2021
    dir: pydata-hamburg-2021
    youtube_list:
      - https://www.youtube.com/playlist?list=PLGVZCDnMOq0qbRG8gBRkosFfhWrObasQF
    related_urls:
      - label: Conference Website
        url: https://www.meetup.com/pydata-hamburg/
    language: eng
    dates:
      begin: 2020-11-03
      end: 2021-03-03
      default: 2021-03-03
    minimal_download: false
    issue: xxx
    overwrite:
      # all: true # takes precedence over add_new_files and existing_files_fields
      add_new_files: true
      existing_files_fields:
        - duration
        - thumbnail_url
        - videos
        - description
        - language
        - recorded
        - related_urls
        - speakers
        - tags
        - title
    tags:

# ISO_639-3 language codes https://en.wikipedia.org/wiki/ISO_639-3

# languages = {
#     'ita': 'Italian',
#     'zho': 'Chinese',
#     'por': 'Portuguese',
#     'ukr': 'Ukrainian',
#     'deu': 'German',
#     'eng': 'English',
#     'rus': 'Russian',
#     'fra': 'French',
#     'spa': 'Spanish',
#     'eus': 'Basque',
#     'cat': 'Catalan',
#     'glg': 'Galician',
#     'kor': 'Korean',
#     'lit': 'Lithuanian',
#     'jpn': 'Japanese',
#     'ces': 'Czech',
#     'pol': 'Polish',
#     'heb': 'Hebrew',
#     'tha': 'Thai',
# }

~~~

Scraped with [pyvideo_scrape](https://github.com/pyvideo/pyvideo_scrape)
---
 pydata-eindhoven-2022/category.json           |  3 ++
 ...to-develop-a-machine-learning-package.json | 39 +++++++++++++++++++
 .../videos/andy-sava-closing-notes.json       | 39 +++++++++++++++++++
 ...ostami-predictive-maintenance-at-asml.json | 39 +++++++++++++++++++
 ...-optimising-ranking-in-online-grocery.json | 39 +++++++++++++++++++
 ...python-package-for-fuzzy-topic-models.json | 39 +++++++++++++++++++
 ...ics-in-the-wild-welcome-to-the-jungle.json | 39 +++++++++++++++++++
 ...er-notebooks-and-a-recipe-to-fix-them.json | 39 +++++++++++++++++++
 ...tour-of-the-many-dataframe-frameworks.json | 39 +++++++++++++++++++
 ...-devcontainer-for-your-python-project.json | 39 +++++++++++++++++++
 ...n-stegeren-practical-code-archaeology.json | 39 +++++++++++++++++++
 ...-while-providing-data-to-the-business.json | 39 +++++++++++++++++++
 ...arijn-markus-ai-for-good-then-and-now.json | 39 +++++++++++++++++++
 ...ta-storytelling-through-visualization.json | 39 +++++++++++++++++++
 ...neration-within-just-eat-takeaway-com.json | 39 +++++++++++++++++++
 ...onalising-a-car-brands-advertisements.json | 39 +++++++++++++++++++
 ...cal-sql-directly-to-your-python-shell.json | 39 +++++++++++++++++++
 .../pydata-eindhoven-2022-aftermovie.json     | 39 +++++++++++++++++++
 ...oducible-machine-learning-experiments.json | 39 +++++++++++++++++++
 ...rence-well-it-is-running-a-greenhouse.json | 39 +++++++++++++++++++
 ...o-full-web-apps-in-no-time-with-taipy.json | 39 +++++++++++++++++++
 ...t-warmerdam-bulk-labelling-techniques.json | 39 +++++++++++++++++++
 ...owering-the-barrier-for-ml-monitoring.json | 39 +++++++++++++++++++
 23 files changed, 861 insertions(+)
 create mode 100644 pydata-eindhoven-2022/category.json
 create mode 100644 pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json
 create mode 100644 pydata-eindhoven-2022/videos/andy-sava-closing-notes.json
 create mode 100644 pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json
 create mode 100644 pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json
 create mode 100644 pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json
 create mode 100644 pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json
 create mode 100644 pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json
 create mode 100644 pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json
 create mode 100644 pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json
 create mode 100644 pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json
 create mode 100644 pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json
 create mode 100644 pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json
 create mode 100644 pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json
 create mode 100644 pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json
 create mode 100644 pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json
 create mode 100644 pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json
 create mode 100644 pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json
 create mode 100644 pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json
 create mode 100644 pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json
 create mode 100644 pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json
 create mode 100644 pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json
 create mode 100644 pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json

diff --git a/pydata-eindhoven-2022/category.json b/pydata-eindhoven-2022/category.json
new file mode 100644
index 000000000..f4cfd5914
--- /dev/null
+++ b/pydata-eindhoven-2022/category.json
@@ -0,0 +1,3 @@
+{
+  "title": "PyData Eindhoven 2022"
+}
diff --git a/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json b/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json
new file mode 100644
index 000000000..4f1689cd1
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nThis talk is about machine learning package development. I will speak about the pains and benefits it causes for developers and share why open sourcing makes the package even better. The talk is not focused on the package itself but rather on common problems so it will be interesting for a wide range of data scientists and python developers.\n\nHave you ever wondered how new open source packages emerge? This talk is exactly about it. I will tell how the idea of a package is born and how it transforms from the proof of concept to the first release version. How business could benefit from it and why the development itself is not the hardest part of open source development. And last but not least, why we changed the architecture of our package three times and why you would too!",
+  "duration": 1687,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/8bc0WJENcSY/maxresdefault.jpg",
+  "title": "Andrei Alekseev - Why does everyone need to develop a machine learning package?",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=8bc0WJENcSY"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/andy-sava-closing-notes.json b/pydata-eindhoven-2022/videos/andy-sava-closing-notes.json
new file mode 100644
index 000000000..e8f0dd04c
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/andy-sava-closing-notes.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.",
+  "duration": 256,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/RWaecaqhZ2o/maxresdefault.jpg",
+  "title": "Andy Sava - Closing Notes",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=RWaecaqhZ2o"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json b/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json
new file mode 100644
index 000000000..82a87359d
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nIn the chip industry, time is money. Customers of ASML\u2019s lithography systems expect high uptimes. But expected and unexpected maintenance is part of that equation, sometimes requiring to halt the production temporarily.\n\nIn this presentation, we show you how we are building and deploying Machine Learning models to predict upcoming maintenance actions within the upcoming three months. Our work helps to boost productivity, maximize system utilization and reduce unexpected workload for ASML\u2019s customer support.\n\nIn the chip industry, time is money. Customers of ASML\u2019s lithography systems expect high uptimes. But expected and unexpected maintenance is part of that equation, sometimes requiring to halt the production temporarily.\n\nIn this presentation, we show you how we are building and deploying Machine Learning models to predict upcoming maintenance actions within the upcoming three months. Our work helps to boost productivity, maximize system utilization and reduce unexpected workload for ASML\u2019s customer support.",
+  "duration": 2375,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/mhXui-2bXz8/maxresdefault.jpg",
+  "title": "Anjan Prasad Gantapara, Hamideh Rostami - Predictive Maintenance at ASML",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=mhXui-2bXz8"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json b/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json
new file mode 100644
index 000000000..253d0b1ce
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nAn ever increasing number of people are discovering mobile grocery shopping as an alternative to brick-and-mortar supermarkets. This talk will cover how we can use machine learning to make these customers' grocery shopping as smooth and frictionless as possible. We do this by applying ML models that rank products in agreement with the customer\u2019s intent: e.g., by detecting personal shopping habits, and by striking a balance between query relevance and margin.\n\nIn online grocery, the wide range of available choices can easily overwhelm a customer. Moreover, failure to find the desired products may lead to customers not converting at all. It\u2019s therefore crucial to optimise ranking, in accordance with the customer\u2019s intent; and to construct sensible algorithms that capture this intended behaviour.\n\nIn this talk, I will provide a holistic view of how we approach ranking in the online grocery context. Depending on an app page\u2019s intended functionality, we might aim to make rebuying as frictionless as possible, while elsewhere we personalise search query relevance while not losing sight of margin. More concretely, I will discuss how we have set up ranking in an explainable and interpretable way that allows for a balance between relevance, profit and any other business-based concerns there might be. In addition, I will briefly discuss three algorithms that we have developed and implemented, and how these are combined to optimise the customer experience:\n- prediction of rebuying probabilities through detecting personal shopping habits\n- construction of unbiased search term-article relevances through structural position bias corrections\n- personalisation of search results while taking profitability into account\n\nThis talk will provide the application-minded Data Scientist with an inside view into the deliberations that inform our ranking algorithms and setup.",
+  "duration": 1832,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/J7qfN8hl4rs/maxresdefault.jpg",
+  "title": "Bas Vlaming - Everything in its Right Place: Optimising Ranking in Online Grocery",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=J7qfN8hl4rs"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json b/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json
new file mode 100644
index 000000000..083bdbcca
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nWe present FuzzyTM, a Python library for training fuzzy topic models and creating topic embeddings for downstream tasks. Its modular design allows researchers to modify each software element and for future methods to be added. Meanwhile, the user-friendly pipelines with default values allow practitioners to train a topic model with minimal effort.\n\nThe volume of data/information created is growing exponentially and forecasted to reach 181 zettabyte by 2025. Approximately 80% of today\u2019s data is composed of unstructured or semi-structured data. Analyzing all this data is time intensive and costly in many cases. One technique to systematically analyze large corpora of texts is topic modeling, which returns the latent topics present in a corpus. Recently, several fuzzy topic modeling algorithms have been proposed and have shown superior results over the existing algorithms. Although various Python libraries offer topic modeling algorithms, none includes fuzzy topic models. Therefore, we present FuzzyTM, a Python library for training fuzzy topic models and creating topic embeddings for downstream tasks. Its modular design allows researchers to modify each software element and for future methods to be added. Meanwhile, the user-friendly pipelines with default values allow practitioners to train a topic model with minimal effort.",
+  "duration": 1691,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/sD-KmuqqYPY/maxresdefault.jpg",
+  "title": "Emil Rijcken - FuzzyTM: a Python package for fuzzy topic models",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=sD-KmuqqYPY"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json b/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json
new file mode 100644
index 000000000..d117e1634
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nAll organizations will need to become data-driven organizations, or they will go the way of the dinosaur. However, AI scales risk to organizational brand and profit. Trustworthy and Ethical AI are no longer luxuries, but business necessities. Let's explore together, why bias is not exclusive to AI, why technology has never been neutral and why Data Science has little to do with Science!\n\nMarc is AI & Ethics lead at KPMG, Managing Consultant, recovering Data Scientist and Public Speaker.\n\n00:00 - Fabian vd Berg - Opening Notes\n08:50 - Marc van Meel - AI Ethics in the Wild - Welcome to the Jungle",
+  "duration": 2822,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/uny310s1olk/maxresdefault.jpg",
+  "title": "Fabian vd Berg - Opening Notes / Marc van Meel - AI Ethics in the Wild - Welcome to the Jungle",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=uny310s1olk"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json b/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json
new file mode 100644
index 000000000..e1c2cc4d0
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nThe most popular data science development tools have largely been developed by academics as scratch pads for interactive data exploration. Jupyter notebooks, for instance, were developed 20 years ago at Berkeley (they were called iPython notebooks at the time). Because of their flexibility and interactivity, these tools have become widespread amongst coding data scientists. More recently, GUI-based tools have begun to be popular. They reduce the technical load on the user, but typically lack much needed flexibility and interoperability. Both avenues of innovation are wildly inadequate for modern data science development. GUI-based tools are typically too expensive, too restrictive, and too closed. The development of automated machine learning tools only made this problem worse, with dozens of software startups urging business analysts to start building machine learning solutions, often with questionable results and even more questionable customer retention metrics. On the other hand, notebook-based solutions are typically too error-prone, too loose, and too isolated to be sufficient. The result is intractable challenges around collaboration, communication, and deployment. The most recent entrants into the notebook space have only marginally improved the experience without fixing the underlying flaws. This talk discusses the fundamental flaws with the way these tools have been developed and how they currently function. Advancement in this space will require reworking the architecture and functionality of these tools at some of the most basic levels. These fixes include things like multiprocessing capabilities; real-time collaboration tools; safe, consistent code execution; easy API deployment; and portable communication tools. Future innovation in the data science development experience will have to tackle these problems and more in order to be successful.\n\nThe most popular data science development tools have largely been developed by academics as scratch pads for interactive data exploration. Jupyter notebooks, for instance, were developed 20 years ago at Berkeley (they were called iPython notebooks at the time). Because of their flexibility and interactivity, these tools have become widespread amongst coding data scientists. More recently, GUI-based tools have begun to be popular. They reduce the technical load on the user, but typically lack much needed flexibility and interoperability. Both avenues of innovation are wildly inadequate for modern data science development. GUI-based tools are typically too expensive, too restrictive, and too closed. The development of automated machine learning tools only made this problem worse, with dozens of software startups urging business analysts to start building machine learning solutions, often with questionable results and even more questionable customer retention metrics. On the other hand, notebook-based solutions are typically too error-prone, too loose, and too isolated to be sufficient. The result is intractable challenges around collaboration, communication, and deployment. The most recent entrants into the notebook space have only marginally improved the experience without fixing the underlying flaws. This talk discusses the fundamental flaws with the way these tools have been developed and how they currently function. Advancement in this space will require reworking the architecture and functionality of these tools at some of the most basic levels. These fixes include things like multiprocessing capabilities; real-time collaboration tools; safe, consistent code execution; easy API deployment; and portable communication tools. Future innovation in the data science development experience will have to tackle these problems and more in order to be successful.",
+  "duration": 2003,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/aeD5ydmrTdY/maxresdefault.jpg",
+  "title": "G. Michaelson - Significant Roadblocks to Usefulness for Jupyter Notebooks and a Recipe to Fix them",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=aeD5ydmrTdY"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json b/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json
new file mode 100644
index 000000000..45048f2bf
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nProcessing tabular data has been of the most common operations for data scientists and engineers for a while now. A few years ago, pandas was the single tool of reference for it, but is it still true today?\nIn this talk, we will review and compare the existing dataframe frameworks to see how they solve the challenges of performance, scalability and user experience.\n\nProcessing tabular data has been of the most common operations for data scientists and engineers for a while now. A few years ago, pandas was the single tool of reference for it, but is it still true today?\n\nThe increase in the size of the datasets and in the diversity of the use-cases has highlighted many challenges regarding performance, scalability and user experience. The ecosystem has evolved to now include many new alternatives, each of them tackling one or more of those dimensions differently. Some of them even put SQL back under the spotlight!\n\nIn this talk we will deep dive into the internals of tabular data processing and look at how the main players of the ecosystem work under the hood. After defining the fundamentals, we will zoom on their APIs and memory models through various examples, so that the audience can get an illustrated comparison between frameworks.",
+  "duration": 2099,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/AMq8qZZwlYc/maxresdefault.jpg",
+  "title": "Harizo Rajaona - A Tour of the Many DataFrame Frameworks",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=AMq8qZZwlYc"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json b/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json
new file mode 100644
index 000000000..8c77a097e
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json
@@ -0,0 +1,39 @@
+{
+  "description": "Devcontainers are an open-source specification, which allow you to connect your IDE to a running Docker container and develop right inside it. This has numerous advantages. Because the dev environment is now formally defined, it is reproducible. This means others can easily reproduce your dev environment, too! This makes it much easier for others to join in on your project, and stay updated with changes to the environment.\n\nIn this talk, you will learn: why you might want to use a Devcontainer for your project (or when not \ud83d\ude09), what exactly a Devcontainer is, and how you can build one for your Python project \ud83d\udc0d.\n\nDevcontainers have been gaining traction lately. Whereas previously the technology existed only in the umbrella of Visual Studio Code, it is now released as an open specification. Such, multiple IDE's could all use the same standard specification, promoting reusability and standardisation. That said, Developers are currently hard at work at pushing the technology to become standardised. Especially for these reasons, this is an exciting time to take a closer look at this new specification, and at what the technology can do for us in general.\n\nSo how will I go about this talk? Let's take a look \ud83d\ude4c\ud83c\udffb.\n\n\ud83d\udcdd Talk setup\nLet's learn about Devcontainers together. This will be the setup of my talk:\n\nWhy Devcontainers? What problem do they aim to solve? Pro's & Con's.\nBuilding a basic Devcontainer from scratch\nOpening up the Devcontainer\nExtending the Devcontainer with more useful features\nCustom VSCode settings\nRunning your CI task in the Devcontainer\nConnecting as a non-root user\nOpening up a port to the Devcontainer\nGoing further \ud83d\udd2e\nMore useful links & resources\nConcluding \u2713\n\ud83c\udfe1 What you will take home\nAt the end of the talk, you will be taking home the following:\n- When it makes sense to create one\n- How you can create one\n- Knowledge on how Devcontainers work\n- A template repo for a Python project Devcontainer",
+  "duration": 2161,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/SLsaCdRAV0U/maxresdefault.jpg",
+  "title": "Jeroen Overschie - How to create a Devcontainer for your Python project \ud83d\udc33",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=SLsaCdRAV0U"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json b/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json
new file mode 100644
index 000000000..583dccaf2
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nCode archaeology is figuring out what a thing is for, who built it, and how you can get it to run again.\nDealing with legacy code artefacts (while under time pressure) is something we data people encounter a lot in daily life. I will tell about my experiences from both a research and software engineering standpoint. After quickly going over some common sense approaches, I will dive deeper into real-world archaeology and digital forensics, and find out what we can learn from these fields to make dealing with old artefacts a bit easier. Expect a mix of code and non-code hacks, with ample pop culture archaeology memes.\n\nContents:\n- Code archaeology: why do we do it, and do we need to bring a hat?\n- The basics: common sense approaches to code archaeology\n- What can we learn from real-world archaeologists?\n- What can we learn from digital forensics?",
+  "duration": 1895,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/5KItp5WJY3o/maxresdefault.jpg",
+  "title": "Judith van Stegeren - Practical code archaeology",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=5KItp5WJY3o"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json b/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json
new file mode 100644
index 000000000..4e6a7da77
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nOther people who use your datasets is nice, but updating the logic behind it could cause breaking dashboards and ML models down the line. In this talk I will explain how to prevent these stressful situations by applying unit testing to your data or preprocessing pipelines in Python.\n\nUnit testing is a testing method that is often used for building software. It helps in building more robust applications, so as a developer you can release with more confidence and less errors in production. But can you use this technique as a data engineer or data scientist for you preprocessing or pipeline code as well?\n\nIt turns out you can! And you can reap the same benefits that software engineers experience, such extra confidence before deployment, in your day-to-day work!\n\nIn this talk I will walk you through the conceptual idea of unit testing for data or preprocessing pipelines and provide an example on how to apply it to a very simple use case that uses Pandas. The example will test some transformations on beer data \ud83d\ude09.\n\nI will walk through a five step process with code examples in Python. That way data scientists and data engineers have practical guidance on how to apply it to their own projects by showing how to:\n- Define what the logic is that you want to test within your project;\n- Refactor your code to separate specific parts in your code;\n- Generate synthetic data for testing purposes;\n- Put your refactored code under tests using Pytest;\n- Set up a CI pipeline in your Git provider in order to test code automatically.",
+  "duration": 1705,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/nH9s0BiHY5g/maxresdefault.jpg",
+  "title": "Lars Hanegraaf - How to not pull your hair out while providing data to the business",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=nH9s0BiHY5g"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json b/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json
new file mode 100644
index 000000000..960bade3c
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nUsing data in new and unexpected ways to solve real problems for real people - from farmers in Africa to refugees and the war in Ukraine\n\n\"AI? Back in my day, we just called it Data and Statistics. And it wasn't sexy at all.\nBut we still did the same thing - we use data to improve people's decision making.\nTo help improve people's lives.\"\n\nAs a Managing Data Scientist, Marijn Markus has over 6 years of experience in the field.\nIn this talk, Marijn Markus will share his views and experience on Data Science\nThe vast differences between theory and practice, the dysfunctionality of organizations,\n\nAnd how Data can be applied to change lives\nFrom burnouts, refugees, farming and fighting crime\nTo the conflict in Ukraine today.",
+  "duration": 2192,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/6p_cJMNrEx0/maxresdefault.jpg",
+  "title": "Marijn Markus - AI for Good- Then and Now",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=6p_cJMNrEx0"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json b/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json
new file mode 100644
index 000000000..7e8c46d9e
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nData is everywhere. It is through analysis and visualization that we are able to turn data into information that can be used to drive better decision making. Out-of-the-box tools will allow you to create a chart, but if you want people to take action, your numbers need to tell a compelling story. Learn how elements of storytelling can be applied to data visualization.\n\nData is everywhere. It is through analysis and visualization that we are able to turn data into information that can be used to drive better decision making. Out-of-the-box tools will allow you create a chart, but if you want people to take action, your numbers need to tell a compelling story.\n\nThis talk will show, through numerous examples, how elements of storytelling can be applied to data visualization to uncover the story hidden in your data.\n\nAdditionally, we'll question how objective data visualizations really are. Seemingly small alterations to a chart, such as the title of point of comparison, may drive the viewer to wildly different conclusions. What can you do to guide viewers towards a specific (positive or negative) conclusion? Can a graph be truly neutral?\n\nThis will leave you both with a better understanding of how graphs should be interpreted, as well as the ability to better convey the meaning of your data through visualization.",
+  "duration": 1857,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/eMGF9AeO-sM/maxresdefault.jpg",
+  "title": "Marysia Winkels - Data Storytelling through Visualization",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=eMGF9AeO-sM"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json b/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json
new file mode 100644
index 000000000..52ced29e4
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nWhen A/B testing is not possible but we are still interested in drawing causal conclusions from our data, we need to resort to quasi-experimental approaches. This is the landscape that Just Eat Takeaway.com is navigating in, where we often have experimental data about a specific city, and are interested in knowing what the effects would be on another city. When we drop the requirement of causality and are merely interested in generating likely scenarios, we can use the power of predictive modelling to our advantage. From predicting likely future scenarios, to generating synthetic order data on a minute-to-minute basis, all is possible using the right statistical tools. Even in the absence of pure experimental data, we are still able to model likely futures. This talk is relevant for data scientists that are interested in the intersection of statistics and predictive modelling, and some basic knowledge about these topics will be assumed. The first half of the presentation (0-15) will talk about quasi-experimental models, the second half (15-30) will talk about scenario and data generation.\n\nWithin Just Eat Takeaway.com we are often interested in knowing the causal effect of a certain treatment, such as a price change or a marketing campaign, on the predicted order volume. However, in the absence of a pure A/B test, we need to be smart. The first half of the presentation (0-15 minutes) will delve deeper into the problem of causal modelling for quasi-experiments. In particular, we will go over some statistical models that are able to estimate the counterfactuals. A counterfactual can be seen as a what-if: What would have happened if we did (or did not) deploy a certain treatment? Some techniques that are used within Just Eat Takeaway.com to solve this problem are difference in difference and synthetic control. We will delve a little deeper into these techniques and show the audience how they can be used to answer our question.\n\nThe second half of the presentation (15-30) will be concerned with scenario generation. If we drop the requirement of causality, and are merely interested in generating scenarios that are historically correlated with our treatment, we can use advanced predictive models to generate several futures for multiple values of our treatment. For example, we could predict several futures of order volume by considering several price changes over time. I will briefly mention a recent promising model that is able to deal with such multivariate time series called the Temporal Fusion Transformer. I will end the presentation with models for synthetic data generation, called Gaussian copulas, that are able to generate realistic order data on a minute to minute basis given the possible futures that we predict. This data can be used to predict how many couriers we would need in a city to successfully fulfil the demand and to estimate what possible hiccups there could be.\n\nThe takeaway of the talk is that even in the absence of pure experimental data, we are still able to model likely futures and to act upon this.",
+  "duration": 1939,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/48iCZP0rYl4/maxresdefault.jpg",
+  "title": "Max Knobbout - Causal inference and scenario generation within Just Eat Takeaway.com",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=48iCZP0rYl4"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json b/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json
new file mode 100644
index 000000000..6d980e272
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nWith targeted ads becoming more prevalent in the digital landscape, we share how we used Thompson sampling and a Hierarchical Bayesian Algorithm that makes its own decisions and serves the right ad to the right audience.\n\nIn this talk, we want to share how we used Thompson sampling and self-learning models to improve targeted advertising and create modular ads that learn and adapt based on real-time data. We want to share how we built a model, connected it to real-time data, and set it up so that it can change and improve during, rather than after, a campaign. We also discuss some challenges you might face when using these models and how you can overcome them.\n\nTargeted ads are becoming more prevalent in the digital landscape. These ads can be less intrusive for consumers while at the same time helping businesses reach their preferred audience more effectively. In the current day and age, this also touches upon privacy and the soon-to-be cookieless era of the internet. So how does targeted advertising work with all these changes? Can we scale targeted ads, delivering them to a large audience while keeping them personal and relevant to the individual?\n\nWe made this possible by combining the knowledge of Data Scientists, Machine Learning Engineers, Marketing Specialists, Creative Developers, and Designers. Through this collaboration we built a Hierarchical Bayesian Algorithm that makes its own decisions and serves the right ad to the right audience.",
+  "duration": 2430,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/a0p3_Nfkko0/maxresdefault.jpg",
+  "title": "N. van Engelenhoven, J. Hamerlinck - Thompson sampling for personalising a car brands advertisements",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=a0p3_Nfkko0"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json b/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json
new file mode 100644
index 000000000..0bff3b899
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nIn this talk, we will present DuckDB. DuckDB is a novel data management system that executes analytical SQL queries without requiring a server. DuckDB has a unique, in-depth integration with the existing PyData ecosystem. This integration allows DuckDB to query and output data from and to other Python libraries without copying it. This makes DuckDB an essential tool for the data scientist. In a live demo, we will showcase how DuckDB performs and integrates with the most used Python data-wrangling tool, Pandas.\n\nThe talk is catered primarily towards data scientists and data engineers. The talk aims to familiarize users with the design differences between Pandas and DuckDB and how to combine them to solve their data-science needs. We will have an overview about five main characteristics of DuckDB. 1) Vectorized Execution Engine, 2) End-to-end Query Optimization, 3) Automatic Parallelism, 4) Beyond Memory Execution, and 5) Data Compression. In addition, users will also experience a live demo of DuckDB and Pandas in a typical data science scenario, focusing on comparing their performance and usability while showcasing their cooperation. The demo is most interesting for an audience familiar with Python, the Pandas API, and SQL.",
+  "duration": 1771,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/2i2nyodhGkk/maxresdefault.jpg",
+  "title": "Pedro Holanda - DuckDB: Bringing analytical SQL directly to your Python shell",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=2i2nyodhGkk"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json b/pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json
new file mode 100644
index 000000000..c21e79013
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json
@@ -0,0 +1,39 @@
+{
+  "description": "www.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.",
+  "duration": 140,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/by8HA__fWKs/maxresdefault.jpg",
+  "title": "PyData Eindhoven 2022 - Aftermovie",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=by8HA__fWKs"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json b/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json
new file mode 100644
index 000000000..1aaa84ece
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nIn machine learning projects we need to experiment in order to find and maintain the best-performing model. While we can do initial prototyping in a Notebook, eventually we need to move towards more structured experiment tracking to facilitate reproducibility of our experiments.\n\nThe open-source DVC library aims to tackle this problem through a Git-based approach to versioning data and artifacts. In this talk we will explore how DVC works, how we can apply it to conduct ML experiments, and how we can use it to become a great Pok\u00e9mon trainer.\n\nEvery data scientist has at one point kept track of their experiments on paper, sticky notes, or in a spreadsheet. But how can we guarantee reproducibility for potentially thousands of experiments over numerous years? Can we figure out which version of a model ran in production six months ago, and what data went into its training?\n\nThe talk is aimed at data scientists and explores best practices for ML projects using a light-hearted topic. Some general knowledge of how ML works is expected, but not necessary to understand the talk. The key concept is reproducibility: how can we track and version not just code, but entire experiments?\n\nDVC is a potential solution for this. The philosophy behind it can be summarized as \"Git for data and models\". I will discuss its concepts and show how it works in practice for a classifier of Pok\u00e9mon sprites.\n\nThe main takeaway will be the importance of reproducibility and a demo on how to achieve this.",
+  "duration": 1860,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/eH758kaFxF4/maxresdefault.jpg",
+  "title": "Rob de Wit - Becoming a Pok\u00e9mon Master with DVC: reproducible machine learning experiments",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=eH758kaFxF4"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json b/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json
new file mode 100644
index 000000000..741944f0f
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nIn this talk I hope to convince you that models are not either predictive or causal, but both perspectives should be combined to solve real world problems. I will use a concrete example of how we automate irrigation in greenhouses at Source.\n\nThe causal revolution has taught us that there is a world beyond generating predictions. We now known that not all ML models are suitable for causal inference and have alternatives like double machine learning for causal inference.\n\nDuring this talk, I hope to convince you that the difference between predictive and causal models is not as clear cut as you might think. Using a concrete example of how we control irrigation in greenhouses using machine learning, I will give an example of how to break down a problem into model components that are more or less predictive or causal. Moreover, I hope to give you some practical guidelines on how to decide whether a predictive or causal approach is more suitable for the components of your model.\n\nOutline:\n- Causality warm-up\n- Explanation of irrigation in greenhouses\n- Demonstration of the caveat with predictive models\n- Demonstration of why feature selection matters more then framework selection\n- Brief introduction in double machine learning (full explanation is beyond the scope of this presentation)\n- Demonstration of why double machine learning does not solve the feature selection problem\n- Optional: link to Judea Pearl's causal graphs\n- Explanation of how to isolate part of the problem where you can use predictive models\n- Explanation how this components come together in our solution for irrigation control at Source\n- General advice on how to identify whether to use a predictive or causal approach\n- Conclusion",
+  "duration": 2090,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/iq1oCZ4SkyQ/maxresdefault.jpg",
+  "title": "Ruben Mak - Is it a predictive model? Is it causal inference? Well... It is running a greenhouse.",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=iq1oCZ4SkyQ"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json b/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json
new file mode 100644
index 000000000..716a11b57
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nIn the Python open-source eco-system, many packages are available that cater to:\n- the building of great algorithms\n- the visualization of data\n- back-end functions\n\nDespite this, over 85% of Data Science Pilots remain pilots and do not make it to the production stage.\nWith Taipy, Data Scientists/Python Developers will be able to build great pilots as well as stunning production-ready applications for end-users.\n\nTaipy provides two independent modules: Taipy GUI and Taipy Core.\n\nIn this talk, we will demonstrate how:\n- Taipy GUI goes way beyond the capabilities of the standard graphical stack: Streamlit, Dash, etc.\n- Taipy Core is simpler yet more powerful than the standard Python back-end stack: Airflow, MLFlow, etc.\n\nInitially, we will present how a complete graphical interface can be programmed using Taipy GUI's low code syntax (in Python).\n\nWe will then introduce Taipy Core's main concepts: pipelines, scenarios, data nodes, tasks, caching, etc. We will create pipelines graphically from Python IDEs and submit these pipelines for execution. These pipelines will then be \"scenario enabled\" to provide powerful what-if analysis for Data Scientists or End-Users.\n\nFinally, complete Python applications integrating Taipy Core and Taipy GUI will be demonstrated.",
+  "duration": 2297,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/FNCF6PX0dbk/maxresdefault.jpg",
+  "title": "Vincent Gosselin - Turning your Data/AI algorithms into full web apps in no time with Taipy",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=FNCF6PX0dbk"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json b/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json
new file mode 100644
index 000000000..ca75c6ca4
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json
@@ -0,0 +1,39 @@
+{
+  "description": "Let's say you've to some unlabelled data and you want to train a classifier. You need annotations before you can model, but because you're time-bound you must stay pragmatic. You only have an afternoon to spend. What would you do?\n\nLet's say you've to some unlabelled data and you want to train a classifier. You need annotations before you can model, but because you're time-bound you must stay pragmatic. You only have an afternoon to spend. What would you do?\n\nIt turns out there are a few techniques that can totally help you with this. You can easily get interesting subset annotated quickly by leveraging:\n\na quick search engine\npre-trained models\nsentence/image embeddings\na trick to generate phrase embeddings\nIn this talk I will explain these techniques for bulk labelling whil I will also highlight some tools to get all of this to work. In particular you'll see:\n\nlunr.py (a lightweight search engine)\nsentimany (a library with pretrained sentiment models)\nembetter (adds pretrained embeddings for scikit-learn)\numap (an amazing dimensionality reduction library)\nspaCy (a great NLP tool)\nsense2vec (phrase embeddings trained on reddit)\nbulk (a user interface for bulk labelling embeddings)\nFor this talk I'll assume you're familiar with scikit-learn and that you've heard of embeddings before.",
+  "duration": 1974,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/Wf80CSqWSiQ/maxresdefault.jpg",
+  "title": "Vincent Warmerdam - Bulk Labelling Techniques",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=Wf80CSqWSiQ"
+    }
+  ]
+}
diff --git a/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json b/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json
new file mode 100644
index 000000000..80494e952
--- /dev/null
+++ b/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json
@@ -0,0 +1,39 @@
+{
+  "description": "PyData Eindhoven 2022\n\nBuilding and fine-tuning models is exciting, but how do you know your model keeps performing in the way you carefully designed it? Bringing your model to production without adding any monitoring is like flying on autopilot, but blindfolded.\n\nAdding a mature monitoring setup to your model deployments can be a daunting tasks that is often pushed off to the bottom of the to-do list, or put off entirely. How can we, Data Scientists and ML Engineers, introduce monitoring earlier in the MLOPS process and make it part of your deployment right from the start? This talk offers a practical setup to implement ML monitoring in your project using Prometheus and other open-source tools.\n\nThe ML ecosystem focuses a lot on getting models to production. However, that should not be the end goal, it\u2019s merely the beginning of extracting real value from your model. During this talk, we will discuss:\n- Why monitoring your ML model is important\n- How traditional software monitoring can be used for ML systems\n- What additional elements are required for ML systems\n- How to recognise data drift and target drift\n- Which tools are promising for ML monitoring\n- A scenario for a minimal monitoring setup using open-source tools",
+  "duration": 2213,
+  "language": "eng",
+  "recorded": "2022-12-02",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/eindhoven2022/"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/uHksXhxAZpU/maxresdefault.jpg",
+  "title": "Wesley Boelrijk - Lowering the barrier for ML monitoring",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=uHksXhxAZpU"
+    }
+  ]
+}

From de7b109467169e4bac6acf53424eee11b0437119 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ezequiel=20Leonardo=20Casta=C3=B1o?=
 <14986783+ELC@users.noreply.github.com>
Date: Thu, 26 Jun 2025 12:21:36 +0000
Subject: [PATCH 2/2] Add speaker information

---
 ...to-develop-a-machine-learning-package.json | 21 ++--------
 .../videos/andy-sava-closing-notes.json       | 39 -------------------
 ...ostami-predictive-maintenance-at-asml.json | 22 ++---------
 ...-optimising-ranking-in-online-grocery.json | 21 ++--------
 ...python-package-for-fuzzy-topic-models.json | 21 ++--------
 ...ics-in-the-wild-welcome-to-the-jungle.json | 21 ++--------
 ...er-notebooks-and-a-recipe-to-fix-them.json | 21 ++--------
 ...tour-of-the-many-dataframe-frameworks.json | 21 ++--------
 ...-devcontainer-for-your-python-project.json | 21 ++--------
 ...n-stegeren-practical-code-archaeology.json | 21 ++--------
 ...-while-providing-data-to-the-business.json | 21 ++--------
 ...arijn-markus-ai-for-good-then-and-now.json | 21 ++--------
 ...ta-storytelling-through-visualization.json | 21 ++--------
 ...neration-within-just-eat-takeaway-com.json | 21 ++--------
 ...onalising-a-car-brands-advertisements.json | 22 ++---------
 ...cal-sql-directly-to-your-python-shell.json | 21 ++--------
 .../pydata-eindhoven-2022-aftermovie.json     | 39 -------------------
 ...oducible-machine-learning-experiments.json | 21 ++--------
 ...rence-well-it-is-running-a-greenhouse.json | 21 ++--------
 ...o-full-web-apps-in-no-time-with-taipy.json | 21 ++--------
 ...t-warmerdam-bulk-labelling-techniques.json | 21 ++--------
 ...owering-the-barrier-for-ml-monitoring.json | 21 ++--------
 22 files changed, 62 insertions(+), 438 deletions(-)
 delete mode 100644 pydata-eindhoven-2022/videos/andy-sava-closing-notes.json
 delete mode 100644 pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json

diff --git a/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json b/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json
index 4f1689cd1..4becb2a00 100644
--- a/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json
+++ b/pydata-eindhoven-2022/videos/andrei-alekseev-why-does-everyone-need-to-develop-a-machine-learning-package.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Andrei Alekseev"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/8bc0WJENcSY/maxresdefault.jpg",
-  "title": "Andrei Alekseev - Why does everyone need to develop a machine learning package?",
+  "title": "Why does everyone need to develop a machine learning package?",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/andy-sava-closing-notes.json b/pydata-eindhoven-2022/videos/andy-sava-closing-notes.json
deleted file mode 100644
index e8f0dd04c..000000000
--- a/pydata-eindhoven-2022/videos/andy-sava-closing-notes.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "description": "PyData Eindhoven 2022\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.",
-  "duration": 256,
-  "language": "eng",
-  "recorded": "2022-12-02",
-  "related_urls": [
-    {
-      "label": "Conference Website",
-      "url": "https://pydata.org/eindhoven2022/"
-    }
-  ],
-  "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
-  ],
-  "thumbnail_url": "https://i.ytimg.com/vi/RWaecaqhZ2o/maxresdefault.jpg",
-  "title": "Andy Sava - Closing Notes",
-  "videos": [
-    {
-      "type": "youtube",
-      "url": "https://www.youtube.com/watch?v=RWaecaqhZ2o"
-    }
-  ]
-}
diff --git a/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json b/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json
index 82a87359d..5415f1de9 100644
--- a/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json
+++ b/pydata-eindhoven-2022/videos/anjan-prasad-gantapara-hamideh-rostami-predictive-maintenance-at-asml.json
@@ -10,26 +10,12 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Anjan Prasad Gantapara",
+    "Hamideh Rostami"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/mhXui-2bXz8/maxresdefault.jpg",
-  "title": "Anjan Prasad Gantapara, Hamideh Rostami - Predictive Maintenance at ASML",
+  "title": "Predictive Maintenance at ASML",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json b/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json
index 253d0b1ce..d85feeea4 100644
--- a/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json
+++ b/pydata-eindhoven-2022/videos/bas-vlaming-everything-in-its-right-place-optimising-ranking-in-online-grocery.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Bas Vlaming"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/J7qfN8hl4rs/maxresdefault.jpg",
-  "title": "Bas Vlaming - Everything in its Right Place: Optimising Ranking in Online Grocery",
+  "title": "Everything in its Right Place: Optimising Ranking in Online Grocery",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json b/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json
index 083bdbcca..58c4eae2e 100644
--- a/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json
+++ b/pydata-eindhoven-2022/videos/emil-rijcken-fuzzytm-a-python-package-for-fuzzy-topic-models.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Emil Rijcken"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/sD-KmuqqYPY/maxresdefault.jpg",
-  "title": "Emil Rijcken - FuzzyTM: a Python package for fuzzy topic models",
+  "title": "FuzzyTM: a Python package for fuzzy topic models",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json b/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json
index d117e1634..a1b49eb09 100644
--- a/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json
+++ b/pydata-eindhoven-2022/videos/fabian-vd-berg-opening-notes-marc-van-meel-ai-ethics-in-the-wild-welcome-to-the-jungle.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Marc van Meel"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/uny310s1olk/maxresdefault.jpg",
-  "title": "Fabian vd Berg - Opening Notes / Marc van Meel - AI Ethics in the Wild - Welcome to the Jungle",
+  "title": "AI Ethics in the Wild",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json b/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json
index e1c2cc4d0..8e67d4f26 100644
--- a/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json
+++ b/pydata-eindhoven-2022/videos/g-michaelson-significant-roadblocks-to-usefulness-for-jupyter-notebooks-and-a-recipe-to-fix-them.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Greg Michaelson"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/aeD5ydmrTdY/maxresdefault.jpg",
-  "title": "G. Michaelson - Significant Roadblocks to Usefulness for Jupyter Notebooks and a Recipe to Fix them",
+  "title": "Significant Roadblocks to Usefulness for Jupyter Notebooks and a Recipe to Fix them",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json b/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json
index 45048f2bf..a9ae1c4eb 100644
--- a/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json
+++ b/pydata-eindhoven-2022/videos/harizo-rajaona-a-tour-of-the-many-dataframe-frameworks.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Harizo Rajaona"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/AMq8qZZwlYc/maxresdefault.jpg",
-  "title": "Harizo Rajaona - A Tour of the Many DataFrame Frameworks",
+  "title": "A Tour of the Many DataFrame Frameworks",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json b/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json
index 8c77a097e..70b0db552 100644
--- a/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json
+++ b/pydata-eindhoven-2022/videos/jeroen-overschie-how-to-create-a-devcontainer-for-your-python-project.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Jeroen Overschie"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/SLsaCdRAV0U/maxresdefault.jpg",
-  "title": "Jeroen Overschie - How to create a Devcontainer for your Python project \ud83d\udc33",
+  "title": "How to create a Devcontainer for your Python project",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json b/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json
index 583dccaf2..d39c43b41 100644
--- a/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json
+++ b/pydata-eindhoven-2022/videos/judith-van-stegeren-practical-code-archaeology.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Judith van Stegeren"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/5KItp5WJY3o/maxresdefault.jpg",
-  "title": "Judith van Stegeren - Practical code archaeology",
+  "title": "Practical code archaeology",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json b/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json
index 4e6a7da77..42cb5793f 100644
--- a/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json
+++ b/pydata-eindhoven-2022/videos/lars-hanegraaf-how-to-not-pull-your-hair-out-while-providing-data-to-the-business.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Lars Hanegraaf"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/nH9s0BiHY5g/maxresdefault.jpg",
-  "title": "Lars Hanegraaf - How to not pull your hair out while providing data to the business",
+  "title": "How to not pull your hair out while providing data to the business",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json b/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json
index 960bade3c..0ef20f5f0 100644
--- a/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json
+++ b/pydata-eindhoven-2022/videos/marijn-markus-ai-for-good-then-and-now.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Marijn Markus"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/6p_cJMNrEx0/maxresdefault.jpg",
-  "title": "Marijn Markus - AI for Good- Then and Now",
+  "title": "AI for Good - Then and Now",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json b/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json
index 7e8c46d9e..51789a02c 100644
--- a/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json
+++ b/pydata-eindhoven-2022/videos/marysia-winkels-data-storytelling-through-visualization.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Marysia Winkels"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/eMGF9AeO-sM/maxresdefault.jpg",
-  "title": "Marysia Winkels - Data Storytelling through Visualization",
+  "title": "Data Storytelling through Visualization",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json b/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json
index 52ced29e4..85d0990db 100644
--- a/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json
+++ b/pydata-eindhoven-2022/videos/max-knobbout-causal-inference-and-scenario-generation-within-just-eat-takeaway-com.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Max Knobbout"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/48iCZP0rYl4/maxresdefault.jpg",
-  "title": "Max Knobbout - Causal inference and scenario generation within Just Eat Takeaway.com",
+  "title": "Causal inference and scenario generation within Just Eat Takeaway.com",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json b/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json
index 6d980e272..72ca0f49f 100644
--- a/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json
+++ b/pydata-eindhoven-2022/videos/n-van-engelenhoven-j-hamerlinck-thompson-sampling-for-personalising-a-car-brands-advertisements.json
@@ -10,26 +10,12 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Nico van Engelenhoven",
+    "Julien Hamerlinck"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/a0p3_Nfkko0/maxresdefault.jpg",
-  "title": "N. van Engelenhoven, J. Hamerlinck - Thompson sampling for personalising a car brands advertisements",
+  "title": "Thompson sampling for personalising a car brands advertisements",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json b/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json
index 0bff3b899..21e11a784 100644
--- a/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json
+++ b/pydata-eindhoven-2022/videos/pedro-holanda-duckdb-bringing-analytical-sql-directly-to-your-python-shell.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Pedro Holanda"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/2i2nyodhGkk/maxresdefault.jpg",
-  "title": "Pedro Holanda - DuckDB: Bringing analytical SQL directly to your Python shell",
+  "title": "DuckDB: Bringing analytical SQL directly to your Python shell",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json b/pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json
deleted file mode 100644
index c21e79013..000000000
--- a/pydata-eindhoven-2022/videos/pydata-eindhoven-2022-aftermovie.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "description": "www.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. \n\nPyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.",
-  "duration": 140,
-  "language": "eng",
-  "recorded": "2022-12-02",
-  "related_urls": [
-    {
-      "label": "Conference Website",
-      "url": "https://pydata.org/eindhoven2022/"
-    }
-  ],
-  "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
-  ],
-  "thumbnail_url": "https://i.ytimg.com/vi/by8HA__fWKs/maxresdefault.jpg",
-  "title": "PyData Eindhoven 2022 - Aftermovie",
-  "videos": [
-    {
-      "type": "youtube",
-      "url": "https://www.youtube.com/watch?v=by8HA__fWKs"
-    }
-  ]
-}
diff --git a/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json b/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json
index 1aaa84ece..7fdfd7056 100644
--- a/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json
+++ b/pydata-eindhoven-2022/videos/rob-de-wit-becoming-a-pokemon-master-with-dvc-reproducible-machine-learning-experiments.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Rob de Wit"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/eH758kaFxF4/maxresdefault.jpg",
-  "title": "Rob de Wit - Becoming a Pok\u00e9mon Master with DVC: reproducible machine learning experiments",
+  "title": "Becoming a Pokémon Master with DVC: reproducible machine learning experiments",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json b/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json
index 741944f0f..c3b7b010f 100644
--- a/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json
+++ b/pydata-eindhoven-2022/videos/ruben-mak-is-it-a-predictive-model-is-it-causal-inference-well-it-is-running-a-greenhouse.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Ruben Mak"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/iq1oCZ4SkyQ/maxresdefault.jpg",
-  "title": "Ruben Mak - Is it a predictive model? Is it causal inference? Well... It is running a greenhouse.",
+  "title": "Is it a predictive model? Is it causal inference? Well... It is running a greenhouse.",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json b/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json
index 716a11b57..75f107209 100644
--- a/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json
+++ b/pydata-eindhoven-2022/videos/vincent-gosselin-turning-your-data-ai-algorithms-into-full-web-apps-in-no-time-with-taipy.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Vincent Gosselin"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/FNCF6PX0dbk/maxresdefault.jpg",
-  "title": "Vincent Gosselin - Turning your Data/AI algorithms into full web apps in no time with Taipy",
+  "title": "Turning your Data/AI algorithms into full web apps in no time with Taipy",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json b/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json
index ca75c6ca4..25fc9de8b 100644
--- a/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json
+++ b/pydata-eindhoven-2022/videos/vincent-warmerdam-bulk-labelling-techniques.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Vincent Warmerdam"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/Wf80CSqWSiQ/maxresdefault.jpg",
-  "title": "Vincent Warmerdam - Bulk Labelling Techniques",
+  "title": "Bulk Labelling Techniques",
   "videos": [
     {
       "type": "youtube",
diff --git a/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json b/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json
index 80494e952..2e0bc2536 100644
--- a/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json
+++ b/pydata-eindhoven-2022/videos/wesley-boelrijk-lowering-the-barrier-for-ml-monitoring.json
@@ -10,26 +10,11 @@
     }
   ],
   "speakers": [
-    "TODO"
-  ],
-  "tags": [
-    "Education",
-    "Julia",
-    "NumFOCUS",
-    "Opensource",
-    "PyData",
-    "Python",
-    "Tutorial",
-    "coding",
-    "how to program",
-    "learn",
-    "learn to code",
-    "python 3",
-    "scientific programming",
-    "software"
+    "Wesley Boelrijk"
   ],
+  "tags": [],
   "thumbnail_url": "https://i.ytimg.com/vi/uHksXhxAZpU/maxresdefault.jpg",
-  "title": "Wesley Boelrijk - Lowering the barrier for ML monitoring",
+  "title": "Lowering the barrier for ML monitoring",
   "videos": [
     {
       "type": "youtube",