The books listed at the top are more recent and show the evolution (one might say the come back) of data science towards deep learning and AI. The books in the other half of this listing have been published and re-published in the last 10 year. Many are encyclopedias, some available online only, yet they are extremely useful resources for the data science beginner or expert.
Other than that, the books below are listed in random order, and cover data science, machine learning, and related topics. The seventh entry below is a meta-list (list of lists) featuring fundamental textbooks by Berkeley, Stanford, Microsoft, and the likes (even our own books).
- Two New Free Books on Machine Learning
- Math of Deep Learning
- Fundamentals of Machine Learning and Deep Learning
- Machine Learning and Deep Learning Textbook – Cornell University
- Free Book: Classification and Regression In a Weekend
- Statistics – New Foundations Toolbox and Machine Learning Recipes
- 40+ Modern Tutorials Covering All Aspects of Machine Learning
- Reference Manual about Pandas
- Handbook of Fitting Statistical Distributions with R – CRC Press, 1,718 pages
- Data Mining: Concepts and Techniques
- Pattern Recognition
- The Elements of Statistical Learning
- Handbook of Computational Statistics
- International Encyclopedia of Statistical Science (3 volumes)
- Handbook of Engineering Statistics – Springer, 1,120 pages
- Encyclopedia of Machine Learning – Springer, 1,030 pages
- Encyclopedia of Mathematics– CRC Press, 3,242 pages
- Methods of Multivariate Statistics
- Handbook of Natural Language Processing
- The Data Mining and Knowledge Discovery Handbook – Springer, 1,383 pages
- Computer Science Handbook – CRC Press, 2,752 pages
- Numerical Recipes – Cambridge University Press
