Published on March 2, 2018 by

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:

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