My books 📚 Here you can acces of all the books I own and I strongly recommend : Mathematics for Machine Learning - Marc Peter Deisenroth The Hundred Page Machine Learning Book - Andriy Burkov Artificial Intelligence : A Modern Approach - Stuart Russel Introduction to Machine Learning - Ethem Alpaydin Machine Learning : A Probabilistic Perspective - Kevin P. Murphy Pattern Recognition and Machine Learning - Christopher M. Bishop Machine Learning Engineering - Andriy Burkov Deep Learning - Ian Goodfellow Understanding Machine Learning : From Theory to Algorithm - Shai Shalev-Shwartz Probability, Statistics, and Random Processes for Electrical Engineering - Alberto Leon-Garcia Data Mining : Concepts and Techniques - Jiawei Han Mining of Massive Datasets - Jure Leskovec Designing Data-Intensive Applications - Martin Kleppmann Watch out : Some books may have new editions. Note : This is not an ordered list Note 2 : Links are pointing on amazon.fr Wish list 📃 The Elements of Statistical Learning: Data Mining, Inference, and Prediction - Trevor Hastie Information Theory, Inference and Learning Algorithms - David J. C. MacKay Reinforcement Learning - Richard S. Sutton Online Ressources 💻 Dive into Deep Learning Mathematics for Machine Learning Deep Learning Machine Learning Engineering Forecasting: Principles and Practice Speech and Language Processing Mat Kelcey recomendations
