Data science tools and other announcements fr...

What if you could simply tell a recommendation system what you want instead of relying on likes, dislikes, and watch history? Kyle Polich talks with Fuyuan Lyu about the DPR framework, which combines large language models and traditional recommender systems to give users direct c ...  Show more

How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a reinforcement learning framework that systematically explores how platforms like TikTok personalize content feeds. The conversation covers ...  Show more

Catherine Nelson, author of the new O'Reilly book, Software Engineering for Data Scientists, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and ...

We are at GenAI saturation, so let’s talk about scikit-learn, a long time favorite for data scientists building classifiers, time series analyzers, dimensionality reducers, and more! Scikit-learn is deployed across industry and driving a significant portion of the “AI” that is ac ...  Show more

Trends in open-source AI: Join Jon Krohn and a panel of data science icons as they discuss the most exciting and concerning developments in open-source AI. Hear insights from Drew Conway, Jared Lander, Emily Zabor, and JD Long on the transformative potential of AI and its future ...  Show more

Jon Krohn joins us for a year-end episode about 2020’s biggest data science breakthroughs and for a big podcast announcement for 2021. In this episode you will learn: Global warming [4:37] Our big podcast announcement [6:57] Who is Jon Krohn? [12:14] Top 3 technological brea ...  Show more