Title: Deep Learning: Foundations and Concepts, Author: Christopher M. Bishop
Title: Understanding Deep Learning, Author: Simon J.D. Prince
Title: Foundations of Data Science, Author: Avrim Blum
Title: Probabilistic Robotics, Author: Sebastian Thrun
Title: Linear Algebra for Data Science, Machine Learning, and Signal Processing, Author: Jeffrey A. Fessler
Title: Foundations of Computer Vision, Author: Antonio Torralba
Title: Pattern Recognition and Machine Learning, Author: Christopher M. Bishop
Title: Linear Algebra and Optimization for Machine Learning: A Textbook, Author: Charu C. Aggarwal
Title: Understanding Machine Learning: From Theory to Algorithms, Author: Shai Shalev-Shwartz
Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Author: Trevor Hastie
Title: Essentials of Generative AI, Author: Takeshi Okadome
Title: Deep Generative Modeling, Author: Jakub M. Tomczak
Title: Mathematics for Machine Learning, Author: Marc Peter Deisenroth
Title: Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Author: Yoav Shoham
Title: Introduction to Machine Learning, fourth edition, Author: Ethem Alpaydin
Title: Bandit Algorithms, Author: Tor Lattimore
Title: Algebraic Geometry and Statistical Learning Theory, Author: Sumio Watanabe
Title: Probabilistic Machine Learning: Advanced Topics, Author: Kevin P. Murphy
Title: Artificial Neural Networks, Author: Seoyun J. Kwon
Title: Computer Vision: Algorithms and Applications, Author: Richard Szeliski

Pagination Links