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
