10 Best Machine Learning Books

10 Best Machine Learning Books
10 Best Machine Learning Books

Over the past few years, machine learning has taken the tech world by storm. People throughout the industry are increasingly looking for ways to master machine learning (and capitalize on this skill). Machine learning books are a great place to start.

There’s lots of content out there, so we’ve narrowed things down to only the best machine learning books.

10 Best Machine Learning Books

  1. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Released in 2019, this deep learning book by Aurélien Géron covers the foundational concepts, tools, and techniques required for building intelligent systems.

You can know more about this book here.

  1. Pattern Recognition & Machine Learning

Though some of the content is now outdated, Christoper Bishop’s influential 2006 work has long been considered one of the best machine learning books on the market.

  1. The Hundred Page Machine Learning Book

If you’re looking for a speedy breakdown of some complex concepts, machine learning expert and natural language processing specialist Andriy Burkov has got you covered.

  1. Deep Learning

This 2015 book by Yeshua Bengio, Ian Goodfellow, and Aaron Courville covers a broad range of ML concepts and has been praised by industry experts, including Elon Musk.

  1. Machine Learning for Absolute Beginners: A Plain English Introduction

As the name suggests, Oliver Theobald’s practical text is among the best choices for complete beginners looking to become literate in the field.

  1. Deep Learning with Python

Considered by some to be the clearest explanation of deep learning out there, this 2017 book by Keras creator and Google AI researcher François Chollet deserves its position at the top.

  1. Introduction to Machine Learning with Python: A Guide for Data Scientists

Authored by Andreas C. Müller and Sarah Guido, this book focuses on teaching practical methods for building machine learning solutions using Python and the sci-kit-learn library.

  1. Machine Learning for Hackers

Despite the name, you don’t need to be a hacker to reap the benefits of this 2012 book jointly written by Drew Conway and John Myles White.

  1. Machine Learning for Dummies

Thanks to a straightforward, no-nonsense approach, John Paul Mueller and Luca Massaron’s ‘Machine Learning for Dummies belong among the best books for beginners.

  1. Python Machine Learning

First published in 2015, Sebastian Rashka’s book promises to help readers unlock deeper insights into Machine Leaning via cutting-edge predictive analytics, and in our opinion it more than delivers.

Our list of best machine learning books is comprehensive but it’s far from exhaustive. If you have a favorite that we forgot to mention let us know in the comments.

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