My booklists for machine learning , deep learning and artificial intelligence

My booklists for machine learning , deep learning and artificial intelligence

Subscribe to my newsletter and never miss my upcoming articles

I am trying to gather a book list for machine learning , deep learning and artificial intelligence. If you have a book that you would like to add to the list , feel free to leave a comment in the comment section below.

Machine Learning books:

An Introduction to Statistical Learning with Applications in R written by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

It is the best textbook for statistical learning and everyone who are learning machine learning must heard about this bible.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction written by Trevor Hastie, Robert Tibshirani, and Jerome Friedman

The ESL book with the new edition exclusively include many new topics covering LAR algorithm, lasso path for logisitic regression, the path algorithm for SVM classifier, google page rank algorithm. It is very up to date and I highly recommend this book in particular.

Pattern Recognition and Machine Learning written by Christopher M. Bishop

The PRML book is the book mainly about Bayesian perspective over machine learning and it is very deep in intuitive explanations with loads of figures. It is very well structured in terms of the concepts but I believe its more suitable for high degree researcher or practitioner. I am still trying to finish it and perhaps try to make some blog posts with it if I have spare time.

Deep Learning books:

Deep Learning with PyTorch written by Eli Stevens, Luca Antiga, and Thomas Viehmann

The publication covers the basic and abstractions of PyTorch library. Pytorch make deep learning more easy to understand without removing advanced features and excellent for build a great model itself.

Deep learning written by Ian Goodfellow, Yoshua Bengio and Aaron Courville

The Deep learning textbook is extremely useful as the authors intend to help students and practitioners to understand the machine learning basics, modern practice of deep networks and the deep learning research and its applications.

Artificial Intelligence books:

Artificial Intelligence: A Modern Approach written by Stuart J. Russell and Peter Norvig

The AIMA book is essential for students ideally for beginners, provides an introduction to the AI field and cover different main areas like "Artificial Intelligence", "Problem solving" , "Knowledge and Reasoning ", "Acting Logially," and "Uncertainty Knowledge and Reasoning". It is something that you don't wanna miss.

I am going to update more on this post if I find any more useful textbook or book that I read and I feel useful and constructive for everyone on the field. Stay Tune and be safe!

I hope you enjoy my post on Hashnode, feel free to drop me an email about anything related to machine learning or artificial intelligence. My email is . You can also check all the codes in my Github or click the following URL: . Please follow my twitter for more updates!

Share this