This course is focused on the question: How do we do matrix computations with acceptable speed and acceptable accuracy? The course is taught in Python with Jupyter Notebooks, using libraries such as scikit-learn and numpy for most lessons, as well as numba and pytorch in a few lessons.
Course materials are available on github:
Course overview blog post:
Taught in the University of San Francisco MS in Analytics (MSAN) graduate program:
Ask questions about the course on our fast.ai forums: http://forums.fast.ai/c/lin-alg