30 Compulsory Books On Machine Learning (ML) and Artificial Intelligence (AI) In 2021

Ever since the data science boom in the market, in the same way, their books especially machine learning and artificial intelligence (AI) books have also spread like a jungle in the market. In such a situation, choosing the right book has become very difficult. In this 30 Compulsory Books On Machine Learning (ML) and Artificial Intelligence (AI) post, we have tried to solve these problems and have given a list of the best machine learning and ai books, in making this list we have prepared after thorough analysis on many criteria such as the content of the book, Quality, Price, Availability, etc.

When you look at this complete list, you will quench your thirst to find the best books on AI, Data Science, Machine Learning (ML) because we have created a huge list that will try to fulfill your needs in every possible way.

Compulsory Books On Machine Learning (ML) and Artificial Intelligence (AI)

Introduction to Machine Learning with Python

If you don’t have lots of knowledge and experience with Python, the book is an excellent place to get started. It is well organized, structured, and easy to follow. It also comes with hands-on examples.

Data Science From Scratch

This updated book shows you how to find the gems in today’s messy glut of data.

Approaching (Almost) Any Machine Learning Problem

The book has a lot of code. If you don't like the code first approach do not buy this book. Making code available on Github is not an option.

Driven: The Race to Create the Autonomous Car

Alex Davies tells the dramatic, colorful story of the quest to develop driverless cars—and the fierce competition between Google, Uber, and other companies in a race to revolutionize our lives.

The Hype Machine

“In September, Sinan Aral published The Hype Machine. Five months later, the book might be described as prophetic: This month alone at least two of Aral’s three predictions have come to fruition.”—New York NAMED ONE OF THE BEST BOOKS OF THE YEAR BY WIRED • LONGLISTED FOR THE PORCHLIGHT BUSINESS BOOK AWARD

Artificial Intelligence

This book is one of the most sought-after textbooks in the field of AI. It goes great with Columbia University's online course on Artificial Intelligence (CSMM.101X) and serves as a handy reference.

How to Create a Mind: The Secret of Human Thought

“It is rare to find a book that offers unique and inspiring content on every page. How to Create a Mind achieves that and more. Ray has a way of tackling seemingly overwhelming challenges with an army of reason, in the end convincing the reader that it is within our reach to create nonbiological intelligence that will soar past our own. This is a visionary work that is also accessible and entertaining.” —Rafael Reif, president, MIT

Advances in Financial Machine Learning

The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting.

Artificial Intelligence: 101 Things You Must Know Today About Our Future

You will learn the answers to 101 questions about artificial intelligence, and also have access to a large number of resources, ideas and tips that will help you to understand how artificial intelligence will change our lives.

Mathematics for Machine Learning

'This book provides great coverage of all the basic mathematical concepts for machine learning. I'm looking forward to sharing it with students, colleagues, and anyone interested in building a solid understanding of the fundamentals.' Joelle Pineau, McGill University, Montreal

Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow

Like its name, the book provides a hands-on approach to learning by doing and covers many beginner and advanced techniques.as well as loaded with tips and tricks for hacking machine learning.

Naked Statistics – Stripping the Dread from the Data

A New York Times bestseller "Brilliant, funny…the best math teacher you never had." —San Francisco Chronicle

Together: AI and Human. On The Same Side

The most important questions connected to AI, AGI and ASI. Real world examples of AI applications and companies. An ideal vision how we could achieve a win-win situation with Artificial Intelligence

I would recommend this book for young adults who are open-minded for a better future.

You Look Like a Thing and I Love You

The book makes where AI is [in terms of evolution] more real.
"Janelle Shane of A.I. Weirdness is awesome."―BoingBoing

The Master Algorithm: How the Quest for the Ultimate

If you are a machine learning engineer then you must read it and if you are not an engineer then you can't afford to miss it. Don't go with the word "Algorithm" in the name, book is very interesting.
"An exhilarating venture into groundbreaking computer science."―Booklist, starred review

AI Superpowers: China, Silicon Valley, and the New World

"Kai-Fu Lee's smart analysis on human-AI coexistence is clear-eyed and a must-read. We must look deep within ourselves for the values and wisdom to guide AI's development." --Satya Nadella, CEO, Microsoft

Make Your Own Neural Network

Tariq Rashid has explained the workings of Artificial Neural Networks very well with right combination of diagrams and mathematics. He also shows how to implement them in Python which is very useful.

Architects of Intelligence: The truth about AI from the people building it

Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community.

Machine Learning for Algorithmic Trading

This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting.

HBR's 10 Must Reads on AI, Analytics, and the New Machine Age

For anyone that wants this book you should understand that this book is what you make of it. If you want to understand the topics you can skim through the pages skipping the details, but if you want to know every tiny aspect of what makes these algorithms run then you'll find them here as well.

Deep Learning with Python

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.

An Introduction to Statistical Learning

This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more.

Machine Learning Mastery With Python

In this mega Ebook written in the friendly Machine Learning Mastery style that you’re used to, learn exactly how to get started and apply machine learning using the Python ecosystem.

Weapons of Math Destruction

Definitely recommend to anyone who is interested how information can be manipulated by so called"management skills"-all in the name of profit!

The AI Advantage

An essential guide to business. ―Forbes

Python Machine Learning

Some books should be our partner for lifetime, this book is one of them. This book is best to learn from the beginning for the person willing to devote his career for research in the Machine Learning and Data Science. This is the Best Guide for everyone willing to gain deep knowledge in this field.

Python Machine Learning

This book has been written specifically for beginners and the simple, step by step instructions and plain language make it an ideal place to start for anyone who has a passing interest in this fascinating subject.

Building Machine Learning Powered Applications

In the jungle of publications about ML, this book provides a unique hands-on and principled set of tools to really get you through a project from start to finish. This book is not about the fad of machine learning but what else comes with it.

Human Compatible

“Sound[s] an important alarm bell . . . Human Compatible marks a major stride in AI studies, not least in its emphasis on ethics. At the book’s heart, Russell incisively discusses the misuses of AI.” —Nature

Pattern Recognition and Machine Learning

"This beautifully produced book is intended for advanced undergraduates, PhD students, and researchers and practitioners, primarily in the machine learning or allied areas...A strong feature is the use of geometric illustration and intuition...This is an impressive and interesting book that might form the basis of several advanced statistics courses. It would be a good choice for a reading group." John Maindonald for the Journal of Statistical Software
If you are after a practitioners guide, or a first ML book for self study, this probably isn't ideal. It assumes significant familiarity with multivariate calculus, probability and basic stats (identities, moments, regression, MLE etc.). The pitch is probably early post-graduate level, but with a few stretching parts.