Title: Deep Learning, Author: Ian Goodfellow
Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Author: Trevor Hastie
Title: Understanding Deep Learning, Author: Simon J.D. Prince
Title: Pattern Recognition and Machine Learning, Author: Christopher M. Bishop
Title: Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies, Author: John D. Kelleher
Title: Algorithms for Decision Making, Author: Mykel J. Kochenderfer
Title: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches, Author: Stefano V. Albrecht
Title: Learning Theory from First Principles, Author: Francis Bach
Title: Data Independence: Reclaiming Privacy in an Era of Evolving Tech, Author: Wes Chaar
Title: Foundations of Computer Vision, Author: Antonio Torralba
Title: Prediction, Learning, and Games, Author: Nicolo Cesa-Bianchi
Title: Patterns, Predictions, and Actions: Foundations of Machine Learning, Author: Moritz Hardt
Title: Probabilistic Machine Learning: Advanced Topics, Author: Kevin P. Murphy
Title: The Deep Learning Revolution, Author: Terrence J. Sejnowski
Title: Machine Learning in Production: From Models to Products, Author: Christian Kastner
Title: Machine Learning and Deep Learning in Neuroimaging Data Analysis, Author: Anitha S. Pillai
Title: Algorithmic Learning in a Random World, Author: Vladimir Vovk
Title: Bayesian Reasoning and Machine Learning, Author: David Barber
Title: AI in Chemical Engineering: Unlocking the Power Within Data, Author: José A. Romagnoli
Title: Fairness and Machine Learning: Limitations and Opportunities, Author: Solon Barocas

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