#426 on Reddit
Linear Algebra: Foundations to Frontiers
edX
3 recommenders · 3 threads · recommended in 2 years, 2018–2019 · score 3.3
A free-to-audit edX course from UT Austin (Robert van de Geijn and collaborators) that teaches linear algebra from the ground up, using a computational approach with Python/PyTorch examples. It is also available as a companion book.
Commenters call it the best in its class for scope and depth and recommend it as the linear algebra foundation for machine learning study.
Mathematicsbeginnerfreeinteractive MOOC#linear algebra#computational linear algebra#pytorch#machine learning prerequisites#van de geijn
Recommendations by year
20182019
By far, I found Linear algebra foundations to frontiers the best in its class for scope as well as depth. https://www.edx.org/course/laff-linear-algebra-foundations-to-frontiers PS - I went through the material. A lot of PyTorch and a lot of examples. Very impressive. I am going to recommend this…
You should enroll in an active online course that has an active discussion forum. I can recommend this course from UT Austin: https://www.edx.org/course/linear-algebra-foundations-to-frontiers, which will start on January 15, 2019. You can audit it for free.
I can certainly talk about statistics and mathematics you would need to start on ML 1. Statistics - You should start definitely start with mathematical statistics. The best book for this is Statistics by David Freedman, however I personally like John E Freund's Mathematical Statistics. If you want…
Check out https://www.edx.org/course/linear-algebra-foundations-to-frontiers