5 best artificial intelligence books in 2019

Table of Contents

• Introduction
• 1. Artificial Intelligence: A Modern Approach
• 2. Deep Learning
• 3. Pattern Recognition and Machine Learning (Information Science and Statistics)
• 4. Deep Learning with Python
• 5. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
• Conclusion

Introduction

In this article, we'll discuss our 5 favorite artificial intelligence books from 2019. Check out our YouTube video if you prefer a visual review:

We have reviewed the top 5 best Artificial Intelligence books available on the Internet. And to be honest, these books were really hard to find. Between the "A.I conspiracy books" and the "how to make money off A.I books", there was really wasn't much left to choose from. These resources are weighted based on trusted community reviews and the quality of the content itself. Because why waste your time on bad content? You won't ever truly understand the field of Artificial Intelligence, nor will you be able to even apply it very well. These books will cover topics like Neural Networks, Mathematical Optimizations, Logic, Probability, and Economics - which are all extremely useful in today's modern world.

1. Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach provides AI algorithm techniques in-detail, from pathfinding to intelligent AI Agent design. If you are looking for one of the best books on A.I, then this is surely a top pick. There is detailed information on building Agents, graph algorithms incl. A* Search, and how to navigate in areas of uncertainty. Great book with lots of content and examples.

2. Deep Learning

Deep Learning is written by a famous ex-Googler, providing a rich and detailed guide into one of A.I's most exciting sub-fields, "Machine Learning". This has to be one of the best machine learning books out there at the moment. In this book, you will learn about Neural Networks and how to construct them for various use-cases. It's been backed by our industry thought-leaders such as Elon Musk who has commented on how compressive this book truly is.

3. Pattern Recognition and Machine Learning (Information Science and Statistics)

Pattern Recognition and Machine Learning (Information Science and Statistics) is a specialty book on the field of pattern recognition. This is a no bs* book that covers scientific topics such as Bayesian methods to build A.I agents. It is truly an outstanding book for its time and first published back in 2006.

4. Deep Learning with Python

Deep Learning with Python combines Deep Learning techniques together with the Python programming language. Python is generally the preferred language for building AI models - as it is highly recognized by many large companies and it supports some exceptional A.I libraries such as Tensorflow to construct A.I agents. This book will get you up to speed with building A.I using Deep Learning. Prior knowledge of Python may be advised.

5. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics) might be one of the best books to gain a solid foundation of statistics, which really is the backbone of many A.I based applications. Stats help to drive the decision-making process of AI such that smart decisions are made. This book is compressive and covers Data Mining, Inference, and Prediction - all relevant and highly applicable today.

Conclusion

In this article, we listed our top 5 artificial intelligence books from 2019. Do you agree with our list?