Artificial Intelligence Books to Read in 2020

Artificial intelligence (AI) is being talked about everywhere these days, and it impacts our lives whether we realize it or not.

This will continue to increase, so now’s a great time to learn more about the subject.

Here are some AI-related books that I’ve read and recommend for you to add to your 2020 reading list!  A shameless plug given that I wrote this book, although I believe it will provide significant value to a wide-ranging audience.

It’s becoming imperative for business leaders to understand artificial intelligence and machine learning at an appropriate level in order to build great data-centric products and solutions.

I wrote AI for People and Business for executives, managers, and non-technical folks interested in leveraging AI successfully within their organization, and to help readers understand the many benefits of AI for both people and business.

I also wrote the book for practitioners interested in a business perspective around AI, and to provide simplified frameworks and models to help readers understand and explain complex concepts related to AI.

Download chapter 1 for free here!   The Master Algorithm presents a great history and overview of machine learning and AI for a non-technical or non-expert reader.

The book really helps the reader understand the many different types of algorithmic approaches to data and computer-based learning and intelligence, along with the advantages and limitations of each algorithmic approach.

It also helps develop ideas and concepts around what is needed for computers to truly exhibit human-like intelligence, which is much harder than most people realize.

  The Hundred-Page Machine Learning Book provides an excellent overview of machine learning for practitioners.

The book covers most areas that a practitioner should know about, and includes an appropriate amount of theory and math without being overly technical or mathematically rigorous.

I think all practitioners should have this book on their bookshelf, and it would also benefit non-practitioners that want to take a deeper dive into all aspects of machine learning.

  Machine Learning Yearning is a great book for practitioners.

It is similar to the hundred-page machine learning book in its broad coverage of machine learning and its application to artificial intelligence, but is written more in a how-to or cookbook style.

The book is also written in a very logical order that closely mimics the typical process that a data scientist or machine learning engineer would follow when working on an end-to-end machine learning project, along with discussing relevant key considerations and tradeoffs.

  Neural Networks and Deep Learning is a very easy to read and understand online book specifically about neural networks and deep learning.

It includes a lot of helpful and great looking images, visualizations, and even videos.

I love the authors writing style and I think that people can learn a lot by reading this book.

  Deep learning is a great book on neural networks and deep learning that provides significant technical rigor around these subjects.

It was written primarily for university students and software engineers interested in learning more about machine learning and artificial intelligence, and is definitely not for those averse to mathematics or statistics.

   There you have it — a reading list for anyone interested in learning more about artificial intelligence and AI-related subjects in 2020.

I hope you enjoy!  Bio: Alex Castrounis is the author of AI for People and Business and founder of InnoArchiTech.

He advises companies of all sizes and industries on using data science, artificial intelligence, and machine learning to innovate and win! For the latest from Alex, subscribe to his newsletter and YouTube channel, follow him on Twitter and LinkedIn, and grab your FREE chapter from his book.


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