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22 Timeless Reference Books

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).

  1. Two New Free Books on Machine Learning
  2. Math of Deep Learning
  3. Fundamentals of Machine Learning and Deep Learning
  4. Machine Learning and Deep Learning Textbook – Cornell University
  5. Free Book: Classification and Regression In a Weekend
  6. Statistics – New Foundations Toolbox and Machine Learning Recipes
  7. 40+ Modern Tutorials Covering All Aspects of Machine Learning
  8. Reference Manual about Pandas
  9. Handbook of Fitting Statistical Distributions with R – CRC Press, 1,718 pages
  10. Data Mining: Concepts and Techniques
  11. Pattern Recognition
  12. The Elements of Statistical Learning
  13. Handbook of Computational Statistics
  14. International Encyclopedia of Statistical Science (3 volumes)
  15. Handbook of Engineering Statistics – Springer, 1,120 pages
  16. Encyclopedia of Machine Learning  – Springer, 1,030 pages
  17. Encyclopedia of Mathematics– CRC Press, 3,242 pages
  18. Methods of Multivariate Statistics
  19. Handbook of Natural Language Processing
  20. The Data Mining and Knowledge Discovery Handbook – Springer, 1,383 pages
  21. Computer Science Handbook – CRC Press, 2,752 pages
  22. Numerical Recipes – Cambridge University Press

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