References

DAgostini03

Giulio D'Agostini. Bayesian reasoning in data analysis: A critical introduction. World Scientific, 2003.

MMK+03

David JC MacKay, David JC Mac Kay, and others. Information theory, inference and learning algorithms. Cambridge university press, 2003. URL: https://www.inference.org.uk/itprnn/book.pdf.

Mar18

Osvaldo Martin. Bayesian Analysis with Python: Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ. Packt Publishing Ltd, 2018. URL: https://github.com/PacktPublishing/Bayesian-Analysis-with-Python-Second-Edition.

Mur12

Kevin P Murphy. Machine learning: a probabilistic perspective. MIT press, 2012.

Poi19

Ian Pointer. Programming pytorch for deep learning: Creating and deploying deep learning applications. O'Reilly Media, 2019.

SB18

Richard S Sutton and Andrew G Barto. Reinforcement learning: An introduction. MIT press, 2018.