Intro to Linear Algebra, the first subject of my Machine Learning Foundations tutorial series, is now available in its entirety! It's three content-rich hours, featuring code demos and exercises, split over a total of 24 YouTube videos.

I released the final Intro to Linear Algebra videos over the past week, all of which are from the Matrix Properties segment of the subject (see the segment intro video below):

Topic 18: The Frobenius Norm
Topic 19: Matrix Multiplication
Topic 20: Symmetric and Identity Matrices
Topic 21: Matrix Multiplication Exercises
Topic 22: Matrix Inversion
Topic 23: Diagonal Matrices
Topic 24: Orthogonal Matrices

The YouTube playlist for the entire Machine Learning Foundations series is here.

The series is full of hands-on code demos in Python (particularly the NumPy, TensorFlow, and PyTorch libraries) and all of the code is available open-source in GitHub.

Please let me know what you think of the series so far as it will shape my creation of the remaining seven subjects. Up next in the series will be the second subject, Linear Algebra II: Matrix Operations. Stay tuned!