Probabilistic Graphical Models: Principles and Applications (Advances in Computer Vision and Pattern Recognition)

Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series)

Deep Learning (Adaptive Computation and Machine Learning series)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)

Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data

Causal Inference in Statistics - A Primer

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Causality: Models, Reasoning and Inference

The Hundred-Page Machine Learning Book

Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning series)