lbaret/my_books

List of the books I have

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