From 7123b7f693c7ebe072f6e6eed1da1b95acfe92e6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ezequiel=20Leonardo=20Casta=C3=B1o?= <14986783+ELC@users.noreply.github.com> Date: Thu, 19 Jun 2025 06:53:36 -0300 Subject: [PATCH 1/2] Scraped pydata-eindhoven-2020 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 # 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...id-bias-in-data-pydata-eindhoven-2020.json | 40 +++++++++++++++++ ...s-based-systems-pydata-eindhoven-2020.json | 40 +++++++++++++++++ ...neural-networks-pydata-eindhoven-2020.json | 40 +++++++++++++++++ ...-detection-from-a-telecom-perspective.json | 40 +++++++++++++++++ 22 files changed, 847 insertions(+) create mode 100644 pydata-eindhoven-2020/category.json create mode 100644 pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json create mode 100644 pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json create mode 100644 pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json create mode 100644 pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json create mode 100644 pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json create mode 100644 pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json create mode 100644 pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json create mode 100644 pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json create mode 100644 pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json create mode 100644 pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json create mode 100644 pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json diff --git a/pydata-eindhoven-2020/category.json b/pydata-eindhoven-2020/category.json new file mode 100644 index 000000000..982682eaf --- /dev/null +++ b/pydata-eindhoven-2020/category.json @@ -0,0 +1,3 @@ +{ + "title": "PyData Eindhoven 2020" +} diff --git a/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json b/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json new file mode 100644 index 000000000..d9868d333 --- /dev/null +++ b/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json @@ -0,0 +1,40 @@ +{ + "description": "PyData Eindhoven 2020\n\nThis talk will discuss the RAPIDS suite of open source software libraries which give you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs. Because its API was deliberately designed to be consistent with existing data science utilities (e.g. Pandas DataFrame, SciKit Learn) its integration in majority of cases is limited to only several lines of code change.\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2014, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/6XzS5XcpicM/maxresdefault.webp", + "title": "Adam Grzywaczewski - RAPIDS: How to accelerate your data science pipeline by orders of magnitude", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=6XzS5XcpicM" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json b/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json new file mode 100644 index 000000000..37ad210ff --- /dev/null +++ b/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json @@ -0,0 +1,40 @@ +{ + "description": "PyData Eindhoven 2020\n\nThis talk answers the question: What makes Julia unique? We explore the design innovations that make Julia stand out from other languages of its generation. We discuss areas where it matters, and how it helps programmers in a wide range of domains. We will see examples of these features making a difference in real life use cases, from finance to biotech to scientific machine learning.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1775, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/tkK4zhuAJms/maxresdefault.webp", + "title": "Avik Sengupta - Productivity and performance in one programming language - A tour of Julia", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=tkK4zhuAJms" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json new file mode 100644 index 000000000..63759b7ae --- /dev/null +++ b/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "www.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1713, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/zAs8EMmvG94/maxresdefault.webp", + "title": "Corinne Vigreux - Interview about Codam Coding College | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=zAs8EMmvG94" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json b/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json new file mode 100644 index 000000000..b5d342a89 --- /dev/null +++ b/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json @@ -0,0 +1,40 @@ +{ + "description": "www.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2055, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/yhrPTiN7Cjw/maxresdefault.webp", + "title": "Daan de Bruin - Fighting COVID with Python | PyData Eindhoven 2021", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=yhrPTiN7Cjw" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json new file mode 100644 index 000000000..7b37ff9e6 --- /dev/null +++ b/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "Having extensive data mining experience but limited Python knowledge I fired up a notebook and started digging into COVID case data from EU CDC. A couple of months later, after visualization, curve fitting, modeling and mapping I developed a coronaradar showing and projecting the spread of infections across the world. Let's have a look together at what I did, no slides, just live code.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3922, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/pW-YYRNeyhA/maxresdefault.webp", + "title": "Damiaan Zwietering - Building a coronaradar | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=pW-YYRNeyhA" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json b/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json new file mode 100644 index 000000000..81abea4f7 --- /dev/null +++ b/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json @@ -0,0 +1,40 @@ +{ + "description": "RADON: DevOps framework to optimally exploit serverless computing technologies | PyData Eindhoven 2020\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2076, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/Jl2s9Emf5JI/maxresdefault.webp", + "title": "Damian Andrew Tamburri - RADON: DevOps framework to optimally exploit serverless computing tech...", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Jl2s9Emf5JI" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json new file mode 100644 index 000000000..f92766c8d --- /dev/null +++ b/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json @@ -0,0 +1,44 @@ +{ + "description": "Stan (https://mc-stan.org) is one of the most popular probabilistic programming languages. This talk will be a high-level talk covering 3 things: why Stan exists, when it's useful, and why I use it (with an example).\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1699, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://mc-stan.org", + "url": "https://mc-stan.org" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/SBmqnd1W_iA/maxresdefault.webp", + "title": "Daniel Lee - Stan: why does it exist? when is it useful? why do I use it? | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=SBmqnd1W_iA" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json b/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json new file mode 100644 index 000000000..76d3eedbf --- /dev/null +++ b/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json @@ -0,0 +1,40 @@ +{ + "description": "PyData Eindhoven 2020\n\nLiberty Global's digital TV platform is a complex graph-based IT system that needs to be constantly monitored to prevent downtime. Anomaly detection and graph analytics support engineers with timely problem identification. We show how we evolve graph deep learning methods such as node embedding and message passing from unsupervised to semi-supervised as root causes are gradually being labeled.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1981, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/_Avui3hkOVA/maxresdefault.webp", + "title": "Dennis Ramondt - Monitoring a TV streaming service with AI - from PageRank to graph convolutions", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=_Avui3hkOVA" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json b/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json new file mode 100644 index 000000000..29fa98084 --- /dev/null +++ b/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json @@ -0,0 +1,40 @@ +{ + "description": "PyData Eindhoven 2021\n\nA challenge in real-world data is, among others, the data understanding part. We propose graphical hypergeometric networks (HNet), a method where associations across variables are tested for significance by statistical inference. HNet learns the Association from datasets with mixed datatypes and with unknown function.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2021, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/0TXdnSPSzZ4/maxresdefault.webp", + "title": "dr.ir. E.Taskesen - Improving the data understanding part by graphical hypergeometric networks", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=0TXdnSPSzZ4" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json new file mode 100644 index 000000000..f1a78b0b5 --- /dev/null +++ b/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "In this presentation, we are going to talk about how we tackle the problem of forecasting time series data for our Real Time Dynamic Pricing service and the challenges we have faced putting into production a real time streaming ML service while adopting an MLOps lifecycle.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1805, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/fOYSk702AHc/maxresdefault.webp", + "title": "Ilias Sarantopoulos - Real-Time ML services: From ideation to production | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=fOYSk702AHc" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json new file mode 100644 index 000000000..35dc56695 --- /dev/null +++ b/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "Learn from a developers perspective how to go from a notebook to production. In this talk we will provide an overview of the steps required to go from code in a notebook to an application running in production.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 3598, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/BobaHtafXm0/maxresdefault.webp", + "title": "Koen Vossen - From notebook to production using flask and heroku | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=BobaHtafXm0" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json new file mode 100644 index 000000000..762a7f0b0 --- /dev/null +++ b/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "Dask developers joined with Python web developers to make Coiled, a global scale service providing managed Dask to everyone, everywhere. This talk describes some of our design constraints, a bit of the architecture, and then goes into examples of what this enables across different parts of the PyData community.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1873, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/gkUSDe4rETE/maxresdefault.webp", + "title": "Matthew Rocklin - Dask at Global Scale with Coiled | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=gkUSDe4rETE" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json new file mode 100644 index 000000000..3290dd9e7 --- /dev/null +++ b/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "If you work with Docker on a regular basis you've probably been told that you should try to keep your container images small. We generally prefer smaller images because they upload faster and take up less disk space.\n\nIn this talk we'll try to build the smallest possible docker image, containing a basic PyData tools stack that includes Matplotlib, Scipy, Numpy and Scikit-learn.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1904, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/Z1Al4I4Os_A/maxresdefault.webp", + "title": "Matthijs Brouns - 10x smaller docker containers for Data Science | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Z1Al4I4Os_A" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json b/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json new file mode 100644 index 000000000..609024b7d --- /dev/null +++ b/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json @@ -0,0 +1,40 @@ +{ + "description": "Artificial intelligence to accelerate MRI scans - Philips & LUMC winners in the fastMRI challenge | PyData Eindhoven 2020\n\nPhilips succesfully participated in the first fastMRI challenge, a competition organized by NYU Langone Health and Facebook AI Resarch, to demonstrate how artificial intellignce can accelerate MRI scanners. In the talk, I will introduce the challenge and the problem, present the winning solution developed by the Philips & LUMC team and the challenge results.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2040, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/5EcfIVbkOiQ/maxresdefault.webp", + "title": "Nicola Pezzotti - Artificial intelligence to accelerate MRI scans - Philips & LUMC winners in the...", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=5EcfIVbkOiQ" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json b/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json new file mode 100644 index 000000000..a77ff360f --- /dev/null +++ b/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json @@ -0,0 +1,40 @@ +{ + "description": "Productionizing an unsupervised machine learning model to understand customer feedback | PyData Eindhoven 2020\n\nHave you ever had to read through over 5,000 open-text feedback responses a month?\n\nOur colleagues at ING do this all the time, spending multiple hours each week. This is why we developed an unsupervised machine learning model that clusters customer feedback with similar meaning using open-source Python libraries.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1774, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/YLTLdEiJcq0/maxresdefault.webp", + "title": "Nikki van Ommeren & Maike Fischer - Productionizing an unsupervised machine learning model to...", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=YLTLdEiJcq0" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json new file mode 100644 index 000000000..a1e7eae3d --- /dev/null +++ b/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "Missing data is a common problem in many application. This talk aims at providing a brief overview on the origin of data missingness as well as covering effective approaches to handle that via some practical examples showing how to use and implement missing data techniques using open source python libraries. This talk suits data and machine learning scientists both in industry and academy.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1584, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/M4CtBKrp59w/maxresdefault.webp", + "title": "Reza Sahraeian - The industrial challenge of missing data | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=M4CtBKrp59w" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json b/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json new file mode 100644 index 000000000..321fb2a99 --- /dev/null +++ b/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json @@ -0,0 +1,40 @@ +{ + "description": "PyData Eindhoven 2020\n\nRise of the internet has created opportunities to specifically target consumers. Counterintuitively, this has resulted in overexposure of users to repetitive ads. In this talk, I will show why this is a result of causality problems using a case study. I will demonstrate how we apply instrumental variables and pymc3 to solve these problems.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1045, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/28QsFSAKyKM/maxresdefault.webp", + "title": "Ruben Mak - The causal problem of overexposure to repetitive ads: instrument variables and pymc3", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=28QsFSAKyKM" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json new file mode 100644 index 000000000..88b50b8e7 --- /dev/null +++ b/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "www.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1483, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/TjLtIDDK3sg/maxresdefault.webp", + "title": "Sundas Khalid - Bias in Data | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=TjLtIDDK3sg" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json new file mode 100644 index 000000000..3f71840c2 --- /dev/null +++ b/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "Back in the old days, it was common to write rule-based systems. Systems that do; data - [rules] -labels.\n\nNowadays, it's much more fashionable to use machine learning instead. Something like; (labels, data) - [model] - rules.\n\nIt might be a good time to ask ourselves, is this a better approach? Or have we lost something while in this transition?\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 2278, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/nJAmN6gWdK8/maxresdefault.webp", + "title": "Vincent Warmerdam - Playing by the Rules-Based-Systems | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=nJAmN6gWdK8" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json new file mode 100644 index 000000000..d0a75cb76 --- /dev/null +++ b/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json @@ -0,0 +1,40 @@ +{ + "description": "As deep learning practitioners, we would like to know what input features are responsible for our model decision and start treating our models as white boxes. In the literature, this problem is known as attribution. During this talk, we discuss this problem and several available solutions that you can start using already now in PyTorch ecosystem.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1628, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/VLTiFtKONlI/maxresdefault.webp", + "title": "Vladimir Osin - Understanding Deep Neural Networks | PyData Eindhoven 2020", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=VLTiFtKONlI" + } + ] +} diff --git a/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json b/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json new file mode 100644 index 000000000..3d9f1ce5a --- /dev/null +++ b/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json @@ -0,0 +1,40 @@ +{ + "description": "PyData Eindhoven 2020\n\nAiming at improving our Net Promoter Score by providing better assistance to our customers and, at the same time, reducing calls and truck rolls, VodafoneZiggo applies Computer Vision to help customers identify their in-home setup. In this talk, we will cover the challenges faced with data collection, our struggles with labelling platforms and how we automated our pipelines.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "duration": 1897, + "language": "eng", + "recorded": "2020-10-07", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/eindhoven2020/schedule/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "speakers": [ + "TODO" + ], + "tags": [ + "Education", + "NumFOCUS", + "Opensource", + "PyData", + "Python", + "Tutorial", + "download", + "learn", + "python 3", + "software", + "syntax" + ], + "thumbnail_url": "https://i.ytimg.com/vi_webp/I-AuUDaWw4k/maxresdefault.webp", + "title": "Wilder Rodrigues - Applying Deep Learning for Object Detection from a Telecom Perspective", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=I-AuUDaWw4k" + } + ] +} From 25d69d40b77828883c2a35709a516f9eaba7b373 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ezequiel=20Leonardo=20Casta=C3=B1o?= <14986783+ELC@users.noreply.github.com> Date: Wed, 25 Jun 2025 22:09:59 +0000 Subject: [PATCH 2/2] Add speaker information --- ...ience-pipeline-by-orders-of-magnitude.json | 18 +++------------- ...-programming-language-a-tour-of-julia.json | 18 +++------------- ...-coding-college-pydata-eindhoven-2020.json | 18 +++------------- ...vid-with-python-pydata-eindhoven-2021.json | 18 +++------------- ...g-a-coronaradar-pydata-eindhoven-2020.json | 18 +++------------- ...lly-exploit-serverless-computing-tech.json | 20 ++++-------------- ...why-do-i-use-it-pydata-eindhoven-2020.json | 18 +++------------- ...i-from-pagerank-to-graph-convolutions.json | 18 +++------------- ...-by-graphical-hypergeometric-networks.json | 18 +++------------- ...n-to-production-pydata-eindhoven-2020.json | 18 +++------------- ...lask-and-heroku-pydata-eindhoven-2020.json | 18 +++------------- ...ale-with-coiled-pydata-eindhoven-2020.json | 18 +++------------- ...or-data-science-pydata-eindhoven-2020.json | 18 +++------------- ...mri-scans-philips-lumc-winners-in-the.json | 20 ++++-------------- ...nsupervised-machine-learning-model-to.json | 21 +++++-------------- ...of-missing-data-pydata-eindhoven-2020.json | 18 +++------------- ...ve-ads-instrument-variables-and-pymc3.json | 18 +++------------- ...id-bias-in-data-pydata-eindhoven-2020.json | 18 +++------------- ...s-based-systems-pydata-eindhoven-2020.json | 18 +++------------- ...neural-networks-pydata-eindhoven-2020.json | 18 +++------------- ...-detection-from-a-telecom-perspective.json | 18 +++------------- 21 files changed, 67 insertions(+), 318 deletions(-) diff --git a/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json b/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json index d9868d333..52b5ba837 100644 --- a/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json +++ b/pydata-eindhoven-2020/videos/adam-grzywaczewski-rapids-how-to-accelerate-your-data-science-pipeline-by-orders-of-magnitude.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Adam Grzywaczewski" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/6XzS5XcpicM/maxresdefault.webp", - "title": "Adam Grzywaczewski - RAPIDS: How to accelerate your data science pipeline by orders of magnitude", + "title": "RAPIDS: How to accelerate your data science pipeline by orders of magnitude", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json b/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json index 37ad210ff..91bf80b65 100644 --- a/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json +++ b/pydata-eindhoven-2020/videos/avik-sengupta-productivity-and-performance-in-one-programming-language-a-tour-of-julia.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Avik Sengupta" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/tkK4zhuAJms/maxresdefault.webp", - "title": "Avik Sengupta - Productivity and performance in one programming language - A tour of Julia", + "title": "Productivity and performance in one programming language - A tour of Julia", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json index 63759b7ae..3789c7e17 100644 --- a/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/corinne-vigreux-interview-about-codam-coding-college-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Corinne Vigreux" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/zAs8EMmvG94/maxresdefault.webp", - "title": "Corinne Vigreux - Interview about Codam Coding College | PyData Eindhoven 2020", + "title": "Interview about Codam Coding College", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json b/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json index b5d342a89..f7269b888 100644 --- a/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json +++ b/pydata-eindhoven-2020/videos/daan-de-bruin-fighting-covid-with-python-pydata-eindhoven-2021.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Daan de Bruin" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/yhrPTiN7Cjw/maxresdefault.webp", - "title": "Daan de Bruin - Fighting COVID with Python | PyData Eindhoven 2021", + "title": "Fighting COVID with Python", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json index 7b37ff9e6..786dbb28d 100644 --- a/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/damiaan-zwietering-building-a-coronaradar-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Damiaan Zwietering" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/pW-YYRNeyhA/maxresdefault.webp", - "title": "Damiaan Zwietering - Building a coronaradar | PyData Eindhoven 2020", + "title": "Building a coronaradar", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json b/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json index 81abea4f7..520d203bf 100644 --- a/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json +++ b/pydata-eindhoven-2020/videos/damian-andrew-tamburri-radon-devops-framework-to-optimally-exploit-serverless-computing-tech.json @@ -1,5 +1,5 @@ { - "description": "RADON: DevOps framework to optimally exploit serverless computing technologies | PyData Eindhoven 2020\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "description": "RADON: DevOps framework to optimally exploit serverless computing technologies\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", "duration": 2076, "language": "eng", "recorded": "2020-10-07", @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Damian Andrew Tamburri" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/Jl2s9Emf5JI/maxresdefault.webp", - "title": "Damian Andrew Tamburri - RADON: DevOps framework to optimally exploit serverless computing tech...", + "title": "RADON: DevOps framework to optimally exploit serverless computing technologies", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json index f92766c8d..9431f8ec6 100644 --- a/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/daniel-lee-stan-why-does-it-exist-when-is-it-useful-why-do-i-use-it-pydata-eindhoven-2020.json @@ -18,23 +18,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Daniel Lee" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/SBmqnd1W_iA/maxresdefault.webp", - "title": "Daniel Lee - Stan: why does it exist? when is it useful? why do I use it? | PyData Eindhoven 2020", + "title": "Stan: why does it exist? when is it useful? why do I use it?", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json b/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json index 76d3eedbf..a713daf1a 100644 --- a/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json +++ b/pydata-eindhoven-2020/videos/dennis-ramondt-monitoring-a-tv-streaming-service-with-ai-from-pagerank-to-graph-convolutions.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Dennis Ramondt" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/_Avui3hkOVA/maxresdefault.webp", - "title": "Dennis Ramondt - Monitoring a TV streaming service with AI - from PageRank to graph convolutions", + "title": "Monitoring a TV streaming service with AI - from PageRank to graph convolutions", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json b/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json index 29fa98084..ccf9f29ba 100644 --- a/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json +++ b/pydata-eindhoven-2020/videos/dr-ir-e-taskesen-improving-the-data-understanding-part-by-graphical-hypergeometric-networks.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "E. Taskesen" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/0TXdnSPSzZ4/maxresdefault.webp", - "title": "dr.ir. E.Taskesen - Improving the data understanding part by graphical hypergeometric networks", + "title": "Improving the data understanding part by graphical hypergeometric networks", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json index f1a78b0b5..d79aae939 100644 --- a/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/ilias-sarantopoulos-real-time-ml-services-from-ideation-to-production-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Ilias Sarantopoulos" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/fOYSk702AHc/maxresdefault.webp", - "title": "Ilias Sarantopoulos - Real-Time ML services: From ideation to production | PyData Eindhoven 2020", + "title": "Real-Time ML services: From ideation to production", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json index 35dc56695..4d529c34b 100644 --- a/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/koen-vossen-from-notebook-to-production-using-flask-and-heroku-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Koen Vossen" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/BobaHtafXm0/maxresdefault.webp", - "title": "Koen Vossen - From notebook to production using flask and heroku | PyData Eindhoven 2020", + "title": "From notebook to production using flask and heroku", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json index 762a7f0b0..b358bd09a 100644 --- a/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/matthew-rocklin-dask-at-global-scale-with-coiled-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Matthew Rocklin" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/gkUSDe4rETE/maxresdefault.webp", - "title": "Matthew Rocklin - Dask at Global Scale with Coiled | PyData Eindhoven 2020", + "title": "Dask at Global Scale with Coiled", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json index 3290dd9e7..a3e0a0da4 100644 --- a/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/matthijs-brouns-10x-smaller-docker-containers-for-data-science-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Matthijs Brouns" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/Z1Al4I4Os_A/maxresdefault.webp", - "title": "Matthijs Brouns - 10x smaller docker containers for Data Science | PyData Eindhoven 2020", + "title": "10x smaller docker containers for Data Science", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json b/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json index 609024b7d..40b67c9b1 100644 --- a/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json +++ b/pydata-eindhoven-2020/videos/nicola-pezzotti-artificial-intelligence-to-accelerate-mri-scans-philips-lumc-winners-in-the.json @@ -1,5 +1,5 @@ { - "description": "Artificial intelligence to accelerate MRI scans - Philips & LUMC winners in the fastMRI challenge | PyData Eindhoven 2020\n\nPhilips succesfully participated in the first fastMRI challenge, a competition organized by NYU Langone Health and Facebook AI Resarch, to demonstrate how artificial intellignce can accelerate MRI scanners. In the talk, I will introduce the challenge and the problem, present the winning solution developed by the Philips & LUMC team and the challenge results.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "description": "Artificial intelligence to accelerate MRI scans - Philips & LUMC winners in the fastMRI challenge\n\nPhilips succesfully participated in the first fastMRI challenge, a competition organized by NYU Langone Health and Facebook AI Resarch, to demonstrate how artificial intellignce can accelerate MRI scanners. In the talk, I will introduce the challenge and the problem, present the winning solution developed by the Philips & LUMC team and the challenge results.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", "duration": 2040, "language": "eng", "recorded": "2020-10-07", @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Nicola Pezzotti" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/5EcfIVbkOiQ/maxresdefault.webp", - "title": "Nicola Pezzotti - Artificial intelligence to accelerate MRI scans - Philips & LUMC winners in the...", + "title": "Artificial intelligence to accelerate MRI scans", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json b/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json index a77ff360f..5108ab652 100644 --- a/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json +++ b/pydata-eindhoven-2020/videos/nikki-van-ommeren-maike-fischer-productionizing-an-unsupervised-machine-learning-model-to.json @@ -1,5 +1,5 @@ { - "description": "Productionizing an unsupervised machine learning model to understand customer feedback | PyData Eindhoven 2020\n\nHave you ever had to read through over 5,000 open-text feedback responses a month?\n\nOur colleagues at ING do this all the time, spending multiple hours each week. This is why we developed an unsupervised machine learning model that clusters customer feedback with similar meaning using open-source Python libraries.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", + "description": "Productionizing an unsupervised machine learning model to understand customer feedback\n\nHave you ever had to read through over 5,000 open-text feedback responses a month?\n\nOur colleagues at ING do this all the time, spending multiple hours each week. This is why we developed an unsupervised machine learning model that clusters customer feedback with similar meaning using open-source Python libraries.\n\n===\nwww.pydata.org\r\n\r\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. \r\n\r\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. 00:00 Welcome!\n00:10 Help us add time stamps or captions to this video! See the description for details.\n\nWant to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps", "duration": 1774, "language": "eng", "recorded": "2020-10-07", @@ -14,23 +14,12 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Nikki van Ommeren", + "Maike Fischer" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/YLTLdEiJcq0/maxresdefault.webp", - "title": "Nikki van Ommeren & Maike Fischer - Productionizing an unsupervised machine learning model to...", + "title": "Productionizing an unsupervised machine learning model to understand customer feedback", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json index a1e7eae3d..5ce57dc13 100644 --- a/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/reza-sahraeian-the-industrial-challenge-of-missing-data-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Reza Sahraeian" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/M4CtBKrp59w/maxresdefault.webp", - "title": "Reza Sahraeian - The industrial challenge of missing data | PyData Eindhoven 2020", + "title": "The industrial challenge of missing data", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json b/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json index 321fb2a99..8a8ea1037 100644 --- a/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json +++ b/pydata-eindhoven-2020/videos/ruben-mak-the-causal-problem-of-overexposure-to-repetitive-ads-instrument-variables-and-pymc3.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Ruben Mak" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/28QsFSAKyKM/maxresdefault.webp", - "title": "Ruben Mak - The causal problem of overexposure to repetitive ads: instrument variables and pymc3", + "title": "The causal problem of overexposure to repetitive ads: instrument variables and pymc3", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json index 88b50b8e7..07fd2bac4 100644 --- a/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/sundas-khalid-bias-in-data-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Sundas Khalid" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/TjLtIDDK3sg/maxresdefault.webp", - "title": "Sundas Khalid - Bias in Data | PyData Eindhoven 2020", + "title": "Bias in Data", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json index 3f71840c2..4064616be 100644 --- a/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/vincent-warmerdam-playing-by-the-rules-based-systems-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Vincent Warmerdam" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/nJAmN6gWdK8/maxresdefault.webp", - "title": "Vincent Warmerdam - Playing by the Rules-Based-Systems | PyData Eindhoven 2020", + "title": "Playing by the Rules-Based-Systems", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json b/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json index d0a75cb76..51e5be321 100644 --- a/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json +++ b/pydata-eindhoven-2020/videos/vladimir-osin-understanding-deep-neural-networks-pydata-eindhoven-2020.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Vladimir Osin" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/VLTiFtKONlI/maxresdefault.webp", - "title": "Vladimir Osin - Understanding Deep Neural Networks | PyData Eindhoven 2020", + "title": "Understanding Deep Neural Networks", "videos": [ { "type": "youtube", diff --git a/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json b/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json index 3d9f1ce5a..ecd74eed7 100644 --- a/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json +++ b/pydata-eindhoven-2020/videos/wilder-rodrigues-applying-deep-learning-for-object-detection-from-a-telecom-perspective.json @@ -14,23 +14,11 @@ } ], "speakers": [ - "TODO" - ], - "tags": [ - "Education", - "NumFOCUS", - "Opensource", - "PyData", - "Python", - "Tutorial", - "download", - "learn", - "python 3", - "software", - "syntax" + "Wilder Rodrigues" ], + "tags": [], "thumbnail_url": "https://i.ytimg.com/vi_webp/I-AuUDaWw4k/maxresdefault.webp", - "title": "Wilder Rodrigues - Applying Deep Learning for Object Detection from a Telecom Perspective", + "title": "Applying Deep Learning for Object Detection from a Telecom Perspective", "videos": [ { "type": "youtube",