This is an ever updating list, and this more of list for myself than to share with people. I have hardly few of these books and all the information is compiled from fellow learners, industry experts, data scientists.

Maths to prepare

  • Essential Math for Data Science - [https://www.amazon.com/Essential-Math-Data-Science-Fundamental/dp/1098102932]

Text book

  • Machine Learning - Mitchell http://www.cs.cmu.edu/~tom/mlbook-chapter-slides.html

  • Hands-On Machine Learning with Scikit-Learn, Keras, &Tensorflow

  • Murphy Machine Learning: A probabilistic perspective

  • Machine Learning and Algorithmic Perspective - Stephen Marsland.

  • Understanding Machine Learning: From Theory to Algorithms Textbook by Shai Ben-David and Shai Shalev-Shwartz (Math heavy).

  • Pattern Recognition and ML by Bishop (Math heavy).

  • Decision Making Under Uncertainty (Used in Stanford 228).

  • Algorithms for Decision Making - Kochenderfer, Wheeler, Wray (Text currently used for Stanford 228).

Other curated list:

  • https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md

  • https://towardsdatascience.com/data-science-and-ai-books-for-2021-b8665856cb9e