737: scikit-learn's Past, Present and Future, with scikit-learn co-founder Dr. Gaël Varoquaux

<p>scikit-learn co-founder Gaël Varoquaux and Jon Krohn are live at the historic Sorbonne in Paris, where they discuss the evolution of scikit-learn. From its origins as a memory-efficient Python implementation of support vector machines to its present-day status as a pivotal resource in machine learning, Gaël paints a vivid picture of its remarkable growth. Join us for a glimpse into scikit-learn&apos;s evolution, the realm of open-source collaboration, and the transformative power of data-driven insights in today&apos;s dynamic data landscape.<br/><br/>This episode is brought to you by <a href='https://gurobi.com/sds'>Gurobi</a>, the Decision Intelligence Leader, by <a href='https://datauniverse2024.com'>Data Universe</a>, the out-of-this-world data conference, and by <a href='http://www.cloudwolf.com/sds'>CloudWolf</a>, the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit <a href='https://jonkrohn.com/podcast'>JonKrohn.com/podcast</a> for sponsorship information.<br/><br/>In this episode you will learn:<br/>• The early beginnings and growth of scikit-learn [05:34]<br/>• Development principles of scikit-learn [18:05]<br/>• How to apply scikit-learn to your ML problem [21:16]<br/>• Resource-efficiency and scikit-learn development [25:32]<br/>• How to contribute to an open-source project like scikit-learn yourself [38:21]<br/>• The future of scikit-learn [51:13]<br/>• Gaël on the social-impact data projects in his Soda lab [1:02:33]<br/>• Why domain expertise and statistical rigor are more important than ever [1:11:24]<br/><br/>Additional materials: <a href='https://www.superdatascience.com/737'>www.superdatascience.com/737</a></p>