From 70e79ec634d1864f30e7f8709e3f5254e98155c3 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 21:42:00 -0300 Subject: [PATCH] Scraped pydata-vermont-2024 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 # 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'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-vermont-2024/category.json | 3 ++ ...g-algorithms-in-sktime-and-skforecast.json | 43 +++++++++++++++++ ...entry-to-spatiotemporal-data-analysis.json | 43 +++++++++++++++++ ...e-language-models-pydata-vermont-2024.json | 43 +++++++++++++++++ ...-workflows-in-jax-pydata-vermont-2024.json | 43 +++++++++++++++++ ...-when-scaling-out-pydata-vermont-2024.json | 43 +++++++++++++++++ ...th-python-and-aws-pydata-vermont-2024.json | 43 +++++++++++++++++ ...science-ecosystem-pydata-vermont-2024.json | 43 +++++++++++++++++ ...is-api-for-python-pydata-vermont-2024.json | 43 +++++++++++++++++ ...erpersonalization-pydata-vermont-2024.json | 43 +++++++++++++++++ ...ng-integer-programming-pydata-vermont.json | 47 +++++++++++++++++++ ...hine-learning-and-llms-pydata-vermont.json | 43 +++++++++++++++++ ...data-vermont-2024-closing-notes-day-1.json | 43 +++++++++++++++++ ...data-vermont-2024-closing-notes-day-2.json | 43 +++++++++++++++++ ...data-vermont-2024-opening-notes-day-2.json | 43 +++++++++++++++++ ...ta-vermont-2024-opening-remarks-day-1.json | 43 +++++++++++++++++ ...alysis-and-classification-with-python.json | 43 +++++++++++++++++ ...of-pydata-vermont-interactive-session.json | 43 +++++++++++++++++ 18 files changed, 738 insertions(+) create mode 100644 pydata-vermont-2024/category.json create mode 100644 pydata-vermont-2024/videos/abhishek-murthy-backtesting-time-series-forecasting-algorithms-in-sktime-and-skforecast.json create mode 100644 pydata-vermont-2024/videos/alex-burnham-keynote-lowering-the-barrier-of-entry-to-spatiotemporal-data-analysis.json create mode 100644 pydata-vermont-2024/videos/bj-hargrave-open-source-community-instruction-tuning-of-large-language-models-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/colin-carroll-the-state-of-bayesian-workflows-in-jax-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/hyukjin-kwon-demystifying-pandas-with-pyspark-when-scaling-out-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/jayce-beta-big-data-engineering-with-python-and-aws-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/jonathan-starr-mapping-the-open-science-ecosystem-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/mary-haley-streamlining-web-based-data-management-with-arcgis-api-for-python-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/mike-del-balso-full-rag-a-modern-architecture-for-hyperpersonalization-pydata-vermont-2024.json create mode 100644 pydata-vermont-2024/videos/mike-musty-optimizing-sales-representative-assignments-using-integer-programming-pydata-vermont.json create mode 100644 pydata-vermont-2024/videos/mo-mcelaney-digital-discrimination-cognitive-bias-in-machine-learning-and-llms-pydata-vermont.json create mode 100644 pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-1.json create mode 100644 pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-2.json create mode 100644 pydata-vermont-2024/videos/pydata-vermont-2024-opening-notes-day-2.json create mode 100644 pydata-vermont-2024/videos/pydata-vermont-2024-opening-remarks-day-1.json create mode 100644 pydata-vermont-2024/videos/sean-p-rogers-introduction-to-machine-learning-for-text-analysis-and-classification-with-python.json create mode 100644 pydata-vermont-2024/videos/the-future-of-pydata-vermont-interactive-session.json diff --git a/pydata-vermont-2024/category.json b/pydata-vermont-2024/category.json new file mode 100644 index 000000000..5aafe98da --- /dev/null +++ b/pydata-vermont-2024/category.json @@ -0,0 +1,3 @@ +{ + "title": "PyData Vermont 2024" +} diff --git a/pydata-vermont-2024/videos/abhishek-murthy-backtesting-time-series-forecasting-algorithms-in-sktime-and-skforecast.json b/pydata-vermont-2024/videos/abhishek-murthy-backtesting-time-series-forecasting-algorithms-in-sktime-and-skforecast.json new file mode 100644 index 000000000..03918b548 --- /dev/null +++ b/pydata-vermont-2024/videos/abhishek-murthy-backtesting-time-series-forecasting-algorithms-in-sktime-and-skforecast.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nBacktesting refers to the process of evaluating a time series forecasting algorithm on historical data by replicating the corresponding real-world scenario. Concurrently, parameters such as the model updating and retraining frequencies are also tuned based on the usecase and relevant computational constraints.\n\nIn this talk, we will review the backtesting of time series algorithms using sktime and skforecast. The two open-source machine learning libraries are popular options for developing and deploying forecasting models. Specifically, the following aspects will be covered.\n\n\u2022 Comparing and contrasting backtesting-related features of the two libraries\n\n\u2022 An overview of the different types of cross-validation schemes for time series forecasting, including expanding and fixed windows\n\n\u2022 Model update and retraining for both direct and recursive multistep forecasts\n\nThe talk is geared toward data scientists that want to systematically evaluate time series forecasting models in varied settings. In addition to gaining an overview of the various aspects, the audience will also learn about the implementation options supported by the two libraries. No prior knowledge about machine learning algorithms for forecasting is needed to attend the talk.\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.\n\n00:00 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": 1836, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/7NXCdfzr5d8/maxresdefault.jpg", + "title": "Abhishek Murthy - Backtesting Time Series Forecasting Algorithms in SKTime and SKForecast", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=7NXCdfzr5d8" + } + ] +} diff --git a/pydata-vermont-2024/videos/alex-burnham-keynote-lowering-the-barrier-of-entry-to-spatiotemporal-data-analysis.json b/pydata-vermont-2024/videos/alex-burnham-keynote-lowering-the-barrier-of-entry-to-spatiotemporal-data-analysis.json new file mode 100644 index 000000000..4a9923ebb --- /dev/null +++ b/pydata-vermont-2024/videos/alex-burnham-keynote-lowering-the-barrier-of-entry-to-spatiotemporal-data-analysis.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nAlthough tools that address rescaling spatial and temporal datasets separately do exist in Python and R, there is currently a gap in this space for users in the life and social sciences who are not computer programmers. Here we focus on developing improved tools to assist users in incorporating spatiotemporal datasets into their research programs through a new piece of software called Spacetime.\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.\n\n00:00 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": 3804, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/4RBAFtaQfcI/maxresdefault.jpg", + "title": "Alex Burnham - Keynote: Lowering the barrier of entry to spatiotemporal data analysis", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=4RBAFtaQfcI" + } + ] +} diff --git a/pydata-vermont-2024/videos/bj-hargrave-open-source-community-instruction-tuning-of-large-language-models-pydata-vermont-2024.json b/pydata-vermont-2024/videos/bj-hargrave-open-source-community-instruction-tuning-of-large-language-models-pydata-vermont-2024.json new file mode 100644 index 000000000..67265673e --- /dev/null +++ b/pydata-vermont-2024/videos/bj-hargrave-open-source-community-instruction-tuning-of-large-language-models-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nImagine what you could do if you could tune Large Language Models (LLMs) with contributions from across your community. There are many popular open LLMs, just look at Hugging Face. Up until now, if a developer wanted to contribute a change to an open LLM, the only practical option was to publish a fork of the model which results in many forks but no version of the model having all or many of the community\u2019s changes. In this session we learn about a new, novel technique using the InstructLab open source project to enable incremental, community contributions to instruction-tune a LLM.\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.\n\n00:00 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": 1653, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/l-Nq2b8Y-mA/maxresdefault.jpg", + "title": "BJ Hargrave- Open Source Community Instruction-tuning of Large Language Models | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=l-Nq2b8Y-mA" + } + ] +} diff --git a/pydata-vermont-2024/videos/colin-carroll-the-state-of-bayesian-workflows-in-jax-pydata-vermont-2024.json b/pydata-vermont-2024/videos/colin-carroll-the-state-of-bayesian-workflows-in-jax-pydata-vermont-2024.json new file mode 100644 index 000000000..4185aff7e --- /dev/null +++ b/pydata-vermont-2024/videos/colin-carroll-the-state-of-bayesian-workflows-in-jax-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nThis talk provides an overview to Bayesian workflows in the JAX ecosystem, and is aimed at both newcomers and experienced practitioners. We will look at the Bayesian workflow, from model specification and prior selection, to choices for inference like MCMC, optimization, and VI, to posterior analysis and validation. We will discuss practical ways to use popular libraries in building modular, efficient workflows.\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.\n\n00:00 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": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/b0_D0BxPYLo/maxresdefault.jpg", + "title": "Colin Carroll - The state of Bayesian workflows in JAX | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=b0_D0BxPYLo" + } + ] +} diff --git a/pydata-vermont-2024/videos/hyukjin-kwon-demystifying-pandas-with-pyspark-when-scaling-out-pydata-vermont-2024.json b/pydata-vermont-2024/videos/hyukjin-kwon-demystifying-pandas-with-pyspark-when-scaling-out-pydata-vermont-2024.json new file mode 100644 index 000000000..d8fbd35d0 --- /dev/null +++ b/pydata-vermont-2024/videos/hyukjin-kwon-demystifying-pandas-with-pyspark-when-scaling-out-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nIn this talk, we'll explore effective strategies for scaling pandas workloads using PySpark. We'll delve into techniques such as the Pandas API on Spark, Python UDFs, Pandas UDFs, and Pandas Function APIs. In addition, this talk covers how to manage dependencies and environment setup seamlessly when transitioning to distributed PySpark cluster, providing insights into optimizing performance and leveraging PySpark features for seamless integration with pandas workflows.\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.\n\n00:00 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": 1380, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/Ff78Y6FXIkw/maxresdefault.jpg", + "title": "Hyukjin Kwon - Demystifying pandas with PySpark when scaling out | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Ff78Y6FXIkw" + } + ] +} diff --git a/pydata-vermont-2024/videos/jayce-beta-big-data-engineering-with-python-and-aws-pydata-vermont-2024.json b/pydata-vermont-2024/videos/jayce-beta-big-data-engineering-with-python-and-aws-pydata-vermont-2024.json new file mode 100644 index 000000000..7659bb70c --- /dev/null +++ b/pydata-vermont-2024/videos/jayce-beta-big-data-engineering-with-python-and-aws-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nLearn about how BETA Technologies leverages Python and AWS to serve trillions of data points to hundreds of engineers on a day-to-day basis.\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.\n\n00:00 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": 1525, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/sSxIRT76DtQ/maxresdefault.jpg", + "title": "Jayce @ BETA - Big Data Engineering With Python and AWS | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=sSxIRT76DtQ" + } + ] +} diff --git a/pydata-vermont-2024/videos/jonathan-starr-mapping-the-open-science-ecosystem-pydata-vermont-2024.json b/pydata-vermont-2024/videos/jonathan-starr-mapping-the-open-science-ecosystem-pydata-vermont-2024.json new file mode 100644 index 000000000..d652c7983 --- /dev/null +++ b/pydata-vermont-2024/videos/jonathan-starr-mapping-the-open-science-ecosystem-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nData, code, software, people, papers, patents, funders, organizations, institutions, consortiums, models, metrics, applications... all of it is critical in a reality where open science practices are not only the status quo, but encouraged, supported, or even incentivized.\n\nJoin in this exploration of the open movement, from open-source to open funding to open data networks. Learn from the experience of the Open Source Science Initiative in their endeavor to map the entirety of the digital knowledge and research ecosystems. Join the conversation by mapping your corner of the digital realm -- the tools you use, the people with whom you interact, and the institutions, organizations, or companies that support you.\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.\n\n00:00 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": 1802, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/7c51njj9JPs/maxresdefault.jpg", + "title": "Jonathan Starr - Mapping the Open Science Ecosystem | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=7c51njj9JPs" + } + ] +} diff --git a/pydata-vermont-2024/videos/mary-haley-streamlining-web-based-data-management-with-arcgis-api-for-python-pydata-vermont-2024.json b/pydata-vermont-2024/videos/mary-haley-streamlining-web-based-data-management-with-arcgis-api-for-python-pydata-vermont-2024.json new file mode 100644 index 000000000..2568bab82 --- /dev/null +++ b/pydata-vermont-2024/videos/mary-haley-streamlining-web-based-data-management-with-arcgis-api-for-python-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nIn a world of web-hosted geospatial content, data management has evolved towards web-based Python automation. Join us to explore Stone Environmental's innovative solutions utilizing ArcGIS Notebooks and the ArcGIS API for Python. Discover how we streamline web-based data updates and data administration across our projects. Investigate how these tools can enhance your workflows and leave with a clear understanding of their potential for your own projects.\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.\n\n00:00 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": 1949, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/hWZzjd9RIws/maxresdefault.jpg", + "title": "Mary Haley - Streamlining Web-based Data Management with ArcGIS API for Python | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=hWZzjd9RIws" + } + ] +} diff --git a/pydata-vermont-2024/videos/mike-del-balso-full-rag-a-modern-architecture-for-hyperpersonalization-pydata-vermont-2024.json b/pydata-vermont-2024/videos/mike-del-balso-full-rag-a-modern-architecture-for-hyperpersonalization-pydata-vermont-2024.json new file mode 100644 index 000000000..2dbffeeb5 --- /dev/null +++ b/pydata-vermont-2024/videos/mike-del-balso-full-rag-a-modern-architecture-for-hyperpersonalization-pydata-vermont-2024.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nTecton, presents \"Full RAG,\" a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.\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.\n\n00:00 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": 1687, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/Vm53RO4G-h0/maxresdefault.jpg", + "title": "Mike Del Balso - Full RAG: A Modern Architecture for Hyperpersonalization | PyData Vermont 2024", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=Vm53RO4G-h0" + } + ] +} diff --git a/pydata-vermont-2024/videos/mike-musty-optimizing-sales-representative-assignments-using-integer-programming-pydata-vermont.json b/pydata-vermont-2024/videos/mike-musty-optimizing-sales-representative-assignments-using-integer-programming-pydata-vermont.json new file mode 100644 index 000000000..6eda36c3c --- /dev/null +++ b/pydata-vermont-2024/videos/mike-musty-optimizing-sales-representative-assignments-using-integer-programming-pydata-vermont.json @@ -0,0 +1,47 @@ +{ + "description": "www.pydata.org\n\nConsider the fictional solar company Acme Inc. Prospective solar panel owners schedule appointments for an Acme Inc. sales representative to visit their home and help sell them solar panels. In addition to sales rep availability and location data, suppose that Acme Inc. also has the ability to predict the expected value of each appointment as a function of the lead (potential solar panel owner) and sales rep.\n\nHow should Acme Inc. assign sales reps to leads to maximize the sum of expected values over all appointments? This talk is concerned with finding an optimal assignment of sales reps to leads using integer programming tools implemented in or-tools https://developers.google.com/optimization.\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.\n\n00:00 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": 1821, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://developers.google.com/optimization.", + "url": "https://developers.google.com/optimization." + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/FCxsuxbHVSA/maxresdefault.jpg", + "title": "Mike Musty - Optimizing sales representative assignments using integer programming | PyData Vermont", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=FCxsuxbHVSA" + } + ] +} diff --git a/pydata-vermont-2024/videos/mo-mcelaney-digital-discrimination-cognitive-bias-in-machine-learning-and-llms-pydata-vermont.json b/pydata-vermont-2024/videos/mo-mcelaney-digital-discrimination-cognitive-bias-in-machine-learning-and-llms-pydata-vermont.json new file mode 100644 index 000000000..383982789 --- /dev/null +++ b/pydata-vermont-2024/videos/mo-mcelaney-digital-discrimination-cognitive-bias-in-machine-learning-and-llms-pydata-vermont.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nOn a global scale we are growing numb to stories in the news about machine learning algorithms causing real-world harm. People's lives and livelihood are affected by the decisions made by machines. Learn about how bias can take root in machine learning algorithms, how the rise of foundation models and Large Language Models (LLMs) have impacted this phenomenon, and ways to overcome it. From the power of open source, to tools built to detect and remove bias in machine learning models, there is a vibrant ecosystem of contributors who are working to build a digital future that is inclusive and fair. Now you can become part of the solution.\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.\n\n00:00 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": 1716, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/hrMarCxLz3M/maxresdefault.jpg", + "title": "Mo McElaney- Digital Discrimination: Cognitive Bias in Machine Learning (and LLMs!) | PyData Vermont", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=hrMarCxLz3M" + } + ] +} diff --git a/pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-1.json b/pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-1.json new file mode 100644 index 000000000..e6bbb7679 --- /dev/null +++ b/pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-1.json @@ -0,0 +1,43 @@ +{ + "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.\n\n00:00 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": 98, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/3Lof5oipXII/maxresdefault.jpg", + "title": "PyData Vermont 2024 Closing Notes, Day 1", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=3Lof5oipXII" + } + ] +} diff --git a/pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-2.json b/pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-2.json new file mode 100644 index 000000000..bb5465da9 --- /dev/null +++ b/pydata-vermont-2024/videos/pydata-vermont-2024-closing-notes-day-2.json @@ -0,0 +1,43 @@ +{ + "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.\n\n00:00 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": 71, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/E39qItY2Myo/maxresdefault.jpg", + "title": "PyData Vermont 2024 Closing Notes, Day 2", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=E39qItY2Myo" + } + ] +} diff --git a/pydata-vermont-2024/videos/pydata-vermont-2024-opening-notes-day-2.json b/pydata-vermont-2024/videos/pydata-vermont-2024-opening-notes-day-2.json new file mode 100644 index 000000000..4029b4dd5 --- /dev/null +++ b/pydata-vermont-2024/videos/pydata-vermont-2024-opening-notes-day-2.json @@ -0,0 +1,43 @@ +{ + "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.\n\n00:00 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": 139, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/b_SEt2i1BLg/maxresdefault.jpg", + "title": "PyData Vermont 2024 Opening Notes, Day 2", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=b_SEt2i1BLg" + } + ] +} diff --git a/pydata-vermont-2024/videos/pydata-vermont-2024-opening-remarks-day-1.json b/pydata-vermont-2024/videos/pydata-vermont-2024-opening-remarks-day-1.json new file mode 100644 index 000000000..6107a3a42 --- /dev/null +++ b/pydata-vermont-2024/videos/pydata-vermont-2024-opening-remarks-day-1.json @@ -0,0 +1,43 @@ +{ + "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.\n\n00:00 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": 703, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/ZQHtWiWtBlI/maxresdefault.jpg", + "title": "PyData Vermont 2024 Opening Remarks, Day 1", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=ZQHtWiWtBlI" + } + ] +} diff --git a/pydata-vermont-2024/videos/sean-p-rogers-introduction-to-machine-learning-for-text-analysis-and-classification-with-python.json b/pydata-vermont-2024/videos/sean-p-rogers-introduction-to-machine-learning-for-text-analysis-and-classification-with-python.json new file mode 100644 index 000000000..5c42d398e --- /dev/null +++ b/pydata-vermont-2024/videos/sean-p-rogers-introduction-to-machine-learning-for-text-analysis-and-classification-with-python.json @@ -0,0 +1,43 @@ +{ + "description": "www.pydata.org\n\nMachine learning allows humans to create a model that can act as an extension of the creator\u2019s mind and classify data based on predetermined categories. Manually tagging thousands of rows of data can often be cumbersome and time consuming. Forming a human-machine relationship to classify data can save researchers time and help catalyze data analysis and classification on projects that would otherwise take an untenable number of working hours.\n\nThis tutorial will teach participants how to use Python for machine learning and text classification, creating a human-machine relationship to process and classify textual datasets. Learn how to use the Natural Language Toolkit (NLTK) to explore data. Use pandas, a Python library with extensive functionality to manipulate data, to clean and manipulate a dataframe (a table in pandas). Participants will also learn how to engineer textual features and build machine learning classification pipelines with SciKitLearn (a popular open source machine learning library). Examples of projects that can be undertaken using these methods include identifying a behavioral health component in police incident narratives, identifying hate speech on Facebook, and identifying wildlife trafficking posts on Twitter. Participants should be familiar with basic python data types and methods of manipulating strings.\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.\n\n00:00 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": 3786, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/_ps6XQXA1lY/maxresdefault.jpg", + "title": "Sean P. Rogers - Introduction to Machine Learning for Text Analysis and Classification with Python", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=_ps6XQXA1lY" + } + ] +} diff --git a/pydata-vermont-2024/videos/the-future-of-pydata-vermont-interactive-session.json b/pydata-vermont-2024/videos/the-future-of-pydata-vermont-interactive-session.json new file mode 100644 index 000000000..8071337c4 --- /dev/null +++ b/pydata-vermont-2024/videos/the-future-of-pydata-vermont-interactive-session.json @@ -0,0 +1,43 @@ +{ + "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.\n\n00:00 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": 1441, + "language": "eng", + "recorded": "2024-07-29", + "related_urls": [ + { + "label": "Conference Website", + "url": "https://pydata.org/vermont2024/" + }, + { + "label": "https://github.com/numfocus/YouTubeVideoTimestamps", + "url": "https://github.com/numfocus/YouTubeVideoTimestamps" + } + ], + "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/F3CNcHB2dDc/maxresdefault.jpg", + "title": "The future of PyData Vermont (Interactive Session)", + "videos": [ + { + "type": "youtube", + "url": "https://www.youtube.com/watch?v=F3CNcHB2dDc" + } + ] +}