The final eight linear algebra videos from my Machine Learning Foundations series are live today! Having covered the fundamentals of linear algebra theory in the preceding videos, we can now apply the theory to ML techniques like data compression, regression, and classification.
The eight new videos are:
It's been an epic personal journey to here. Starting with the first linear algebra video in July of last year, there are now a total of 48 videos in my ML Foundations series — over seven hours of content that constitute the first quarter of the series. Up next are several dozen videos on calculus, which will form the second quarter of content. (Probability/stats will be the third quarter and computer science the fourth.)
The playlist for my entire ML Foundations series is here. The series is full of hands-on demos in Python (particularly the NumPy, TensorFlow, and PyTorch libraries) and all of the code is available open-source in GitHub.