A Gigantic List of must-have Machine Learning Books


If you are interested in Machine Learning or Deep Learning, but struggling to decide which book to use to study the same, here is a list of the best books in these fields. What makes this list even better is that some of these books are available online, for free! So go through the list, and pick the one that suits you best.

1. Deep Learning Book
– by Aaron Courville, Ian Goodfellow, and Yoshua Bengio
This book covers them all, including the mathematics required for Deep Learning. What’s more, it is available for free from the official website of this book. This is a must have for any serious Deep Learning practitioner.

2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
– by Aurelien Geron
One of the best books for learning Machine Learning and Deep Learning using Keras and Tensorflow. This even has a separate chapter where you will learn how to work on an end-to-end Machine Learning project.

3. Pattern Recognition and Machine Learning
– by Christopher Bishop
The field of pattern recognition has undergone substantial development over the years. This book reflects these developments while providing a grounding in the basic concepts of pattern recognition and machine learning.

4. Deep Learning with Python
– by François Chollet
This book comes from the creator of Keras, there is a new edition available now which includes additional materials like Deep Learning in Production.

5. Data Science from Scratch
– by Joel Grus
Learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

6. Think Stats
– by Allen B. Downey
This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. It is available here for free.

7. Introduction to Machine Learning with Python: A Guide for Data Scientists
– by Andreas C. Müller and Sarah Guido
If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.

8. The Hundred-Page Machine Learning Book
– by Andriy Burkov
Machine Learning simplified within a 100 pages. But even within these 100 pages, the author describes all the important details.

9. Artificial Intelligence: A Modern Approach
– by Peter Norvig and Stuart J. Russell
Also known as the AI Bible, this book will expand your perspective on Artificial Intelligence. The latest edition was released in 2020.

10. Machine Learning
– by Tom M Mitchell
The study of Machine Learning is incomplete without this book. Although it might seem a little outdated, the concepts are still explained in the simplest manner possible.

11. Dive in Deep Learning
– by Zhang, Lipton, Li, and Smola
This book covers all the important aspects of Deep Learning in three different languages, MXNet, Pytorch, and Tensorflow. It is also available for free from their official website.