My Machine Learning Foundations tutorial series – as suggested by the diagram above – covers Linear Algebra, Calculus, Probability/Stats, and Computer Science (more detail on the series is available in GitHub).

Last month, with a big sigh of joy, I finished recording the last Linear Algebra video for the series, meaning that my filming journey for the first quarter of the ML Foundations series is now complete. I've recorded the footage three different ways:

If you have a subscription to the O'Reilly learning platform, a studio-recorded version has been available since late December as my complete, standalone Linear Algebra for Machine Learning curriculum.
If you have a subscription to the Ai+ training platform, live recordings of my entire linear algebra curriculum are available to view there on-demand as of January.
The first half of my linear algebra content is available on my YouTube channel and via my Udemy course today. This is the version I finished filming most recently. My producer Sangbin is currently editing these videos and I'll post here as they’re released (I recommend signing up for my email newsletter on my homepage to be pushed notifications).

With Linear Algebra in my rear-view mirror, I’m currently tackling the Calculus content. The studio-recorded version of my calculus materials is currently available as a “sneak peak” in O'Reilly. I'm teaching my calculus materials live in the Ai+ platform from now through February 24th. And calculus videos should be published on YouTube and in my Udemy course in March and April.