The "Machine Learning Foundations" video series is here!

Today I released the first videos of my popular Machine Learning Foundations series onto YouTube. It covers all the math and computer science needed to be an outstanding ML practitioner. 

Since May, I've been launching the content as live 3.5-hour webinars in the O'Reilly online learning platform and the response has been overwhelmingly positive, with classes garnering over 1200 registrations each and net promoter scores above 90%. In all, the series consists of eight of these 3.5-hour classes covering linear algebra, calculus, probability, statistics, algorithms, data structures, and optimization. (More detail on the series in GitHub here.)

As of this morning, thanks to superb editing from the talented Sangbin Lee, we're rolling out all of the content in the series as free YouTube videos.

A short welcome video is featured above, while the first true tutorial, on "What Linear Algebra Is", is featured below.

The playlist for the entire series, which will consist of 30+ hours of videos, is here.

Finally, the series is full of hands-on demos in Jupyter notebooks featuring Python, PyTorch, and TensorFlow code, and all of it is available via the GitHub link above.

More videos to come soon...