Six new YouTube videos from my Machine Learning Foundations series are live today! These round out a thematic segment of linear algebra videos focused on matrix determinants, eigenvectors, and eigenvalues.
The specific videos are:
Up next will be a few videos that focus on real-world, hands-on applications of linear algebra to ML problems, including with singular value decomposition, Moore-Penrose pseudoinversion, and principal component analysis. That will wrap up all of the linear algebra content in the series and then we'll move on to calculus!
The playlist for my entire Machine Learning Foundations series is here.
The series is full of hands-on demos in Python and all of the code is available open-source in GitHub.