"Deep Learning: Foundations and Concepts"

"Probabilistic Machine Learning: An Introduction"

"Probabilistic Machine Learning: Advanced Topics" 

"Dive into Deep Learning"

Advanced Deep Learning with Keras: https://github.com/wikibook/keras 

Deep Learning Online Book: https://atcold.github.io/pytorch-Deep-Learning/en/week10/10-1/ 

Understanding Deep Learning: https://udlbook.github.io/udlbook/?fbclid=IwAR3scFHOgKveVupRHk4L13_qp__t5kBE1nQMMaPHrIlTBCSH03RR6cSZiRA 

Computer Science Book: https://github.com/qqqil/ebooks 

Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Mathematics for Machine Learning. Cambridge University Press, 2020. https://mml-book.github.io/  

Aston Zhang, Zack C. Lipton, Mu Li and Alex J. Smola. Dive into Deep Learning. 2019. https://en.d2l.ai/d2l-en.pdf 

Ian Goodfellow, Yoshua Bengio and Aaron Courville. Deep Learning (2016) http://www.deeplearningbook.org/ 

Thomas A. Garrity, All the Math You Missed (But Need to Know for Graduate School) (2021) 2nd Edition. https://www.cambridge.org/ca/academic/subjects/mathematics/recreational-mathematics/all-math-you-missed-need-know-graduate-school-2nd-edition 

Stephen Boyd and Lieven Vandenberghe. Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares. Cambridge University Press, 2018. http://vmls-book.stanford.edu/ 

Michael Nielsen, Neural Networks and Deep Learning (2019). http://neuralnetworksanddeeplearning.com/ 

Garrett Thomas, Mathematics for Machine Learning, University of Berkeley (2018). https://gwthomas.github.io/docs/math4ml.pdf 

Ian Goodfellow, Yoshua Bengio and Aaron Courville, Deep Learning (2016). http://deeplearningbook.org 

Trevor Hastie, Robert Tibshirani and Jerome Friedman, Elements of Statistical Learning (2nd edition, 2009). https://web.stanford.edu/~hastie/ElemStatLearn/ 

Hal Daume III, A Course in Machine Learning (2017). http://ciml.info/ 

Christopher Bishop, Pattern Recognition and Machine Learning (2006). https://www.microsoft.com/en-us/research/people/cmbishop/?#!prml-book 

Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, Foundations of Machine Learning (2012). https://cs.nyu.edu/~mohri/mlbook/ 

Shai Shalev-Shwartz, Shai Ben-David, Understanding Machine Learning: From Theory to Algorithms (2014). http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/ 

Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (3rd Edition) (2010). http://aima.cs.berkeley.edu/ 

Kevin Murphy, Machine Learning: A Probabilistic Perspective (2012). https://www.cs.ubc.ca/~murphyk/MLbook/ 

Ke-Lin Du, M. N. S. Swamy, Neural Networks and Statistical Learning (2019). https://link.springer.com/content/pdf/10.1007%2F978-1-4471-7452-3.pdf