Free Data Science Books 

Some free eBook and resources to learning Data Science

1- Data Science at the Command Line by Jeroen Janssens

2- Deep Learning on Graphs by Yao Ma and Jiliang Tang

3- Hands-on Machine Learning with Scikit-learn, Keras and Tensorflow by Aurelien Geron

4- Practical Statistics for Data Science by Peter Bruce & Andrew Bruce

5-An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

6-Learning Deep Architectures for AI by Yoshua Bengio

7- Python for Data Science Handbook by Jake VanderPlas

8- The Hundred-Page Machine Learning Book by Andriy Burkov.

9- A Course in Machine Learning by Hal Daumé III

10- Intuitive ML and Big Data in C++, Scala, Java, and Python by Kareem Alkaseer

11- Python Notes for Professionals book

12- Learning Pandas

13- Machine Learning – A First Course for Engineers and Scientists by Andreas Lindholm, Niklas Wahlström, Fredrik Lindsten, and Thomas B. Schön

14- Dive into Deep Learning by Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola

15- A Comprehensive Guide to Machine Learning Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang, Jennifer Listgarten, Anant Sahai

16- Data Mining and Analysis by Mohammed J. Zaki and Wagner Meira Jr.

17- SQL Notes for Professionals book

18- Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI by Shlomo Kashani, Amir Ivry

19- Understanding Machine Learning: From Theory to Algorithms by Shai Shalev-Shwartz and Shai Ben-David

20-Algorithms Notes for Professionals book

21-Bayesian Reasoning and Machine Learning by David Barber

22- 800+ Q&As about: Stats, Python, ML, DL, NLP, CV, MLOps by Steve Nouri

23- An Introduction/A History of Data Science

24- Introduction to Machine Learning by Alex Smola and S.V.N. Vishwanathan

25- Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

26- Natural Language Processing with Python by Steven Bird, Ewan Klein, and Edward Loper

27- Learn Python the Right Way by Peter Wentworth, Jeffrey Elkner, Allen B. Downey, and Chris Meyers

28- Pandas: Powerful Python Data Analysis Toolkit by Wes McKinney and the Pandas Development Team

29- Neural Networks and Deep Learning by Michael Nielsen

30- Automate the Boring Stuff with Python by Al Sweigart

31- Patterns, Predictions, and Actions; A story about machine learning by Moritz Hardt and Benjamin Recht

32- Advanced Excel by Towson University

33- The Data Science Handbook by Carl Shan, Henry Wang, William Chen, and Max Song

34- Kubernetes Up and Running by Brendan Burns, Joe Beda & Kelsey Hightower

35- Introducing MLOps by Mark Treveil, Nicolas Omont, Clement Stenac, Kenji Lefevre, Du Phan