Mathematics of Artificial Intelligence

The class contains: 

- foundations of linear algebra, calculus, probability and statistics

- linear models 

- numerical methods for optimization 

- central machine learning problems 

Recommended literature:

- Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong:
Mathematics for Machine Learning. Cambridge University Press.
2020.

- Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning, MIT Press, 2016 

- Howard Anton, Chris Rorres, Anton Kaul: Elementary Linear
Algebra. Wiley. 2019.

Useful information (Including code, videos, etc) can be found under this link: https://mml-book.github.io/external.html