Best Machine Learning Books to read for Beginners & Experts

Machine Learning has bought us the power to run tasks in an automated manner. It has become one of the hottest domains of Computer Science and every large company is applying or thinking of it to apply in the mere future to solve their problems. Machine Learning has a wider scope and its applications are in almost all fields right from space research to Digital Marketing.

It forms the basis for Artificial Intelligence. However, it is not grown to that level where a machine can take decisions on its own. But, the days are not so far and the opportunities, possibilities generated along the way are endless. To help you through we have listed some of the Best Machine Learning Books by which you can learn the concepts easily.

To make it simple for you we have curated a list of the Best Books for Machine Learning for both beginners, Tech Whiz Kids. All the books presented below are extremely popular and you can choose the ones based on your learning sensibilities. Go through a couple of ML Books present and solve your challenges in no time.

Best Machine Learning Books for Beginners

Machine Learning is an insanely popular choice as of now. Let’s get deep into the article and learn about some of the simple Machine Learning Books for Beginners initially.

Machine Learning For Absolute Beginners: A Plain English Introduction (2nd Edition)

Want to learn about Machine Learning and don’t know where to begin your journey with? Let’s help you get started!! Before starting Machine Learning learn some of the important theoretical and statistical principles. This book gives a practical and high-level introduction to Machine Learning for Absolute Beginners too. In fact, it will give you an idea on how to download tools and free data sets, ML Libraries that you will need.

This book includes topics like Data scrubbing techniques, Clustering, Bias/Variance, Regression analysis,  Basics of Neural Networks, Decision Trees, etc. It is one of the best books to begin your preparation and lay a stronger foundation for the concepts of Machine Learning.

  • Paperback: 156 pages
  • Publisher: Independently Published (1 January 2018)
  • Language: English

Machine Learning (in Python and R) For Dummies (1st Edition)

For common people, Machine learning can be a mind boggling concept and for those who know it, it is invaluable. This book aims to help readers be familiar with the theories and concepts of Machine Learning in an easy way. It even focuses on practical, real-world applications of  Machine Learning.

The ML Book from John Paul Mueller and Luca Massaron utilizes R code and Python to demonstrate machines find patterns, analyze results. The Book even covers how ML facilitates web search results, real-time ads on web pages, automation or even spam filtering. You will learn how to code in R using R Studio and Python using Anaconda.

  • Paperback: 432 pages
  • Publisher: John Wiley & Sons; 1 edition (19 July 2016)
  • Language: English

Machine Learning for Hackers: Case Studies and Algorithms to Get you Started

If you are a programmer and interested in data crunching this book is for you. You can learn Machine Learning using hands-on case studies rather than boring math-heavy presentations.  Machine Learning for Hackers focuses on Specific problems like classification, optimization, prediction, and recommendation.

You can even analyze different sample datasets, simple algorithms in the R Programming Language. Instead of using the Mathematical Theory of Machine Learning this book uses various real-life examples to make ML understanding easier and faster.

  • Paperback: 340 pages
  • Publisher: Shroff; First edition (2012)
  • Language: English

Machine Learning: The New AI (The MIT Press Essential Knowledge Series)

Machine Learning has an insane range of applications in modern times from product recommendations to voice recognition. The basis of ML is now data and with data growing bigger it is no surprise that ML is also advanced as ML is the basic in converting data to knowledge.

New AI relies on basic Machine Learning right from evolution to important learning algorithms and example applications. It covers concepts like pattern recognition, reinforcement learning, artificial neural networks, data science, and the ethical and legal implications.

  • Paperback: 224 pages
  • Publisher: MIT Press; Latest Edition edition (11 November 2016)
  • Language: English

Also, Refer: Python Books

Best ML Books for Intermediates/ Experts

Below is the compilation of the best books for Machine Learning and to brush up the concepts. Refer to them and pick the book based on your learning abilities.

Pattern Recognition and Machine Learning (1st Edition)

If you wanted to dive deep into the mysterious world of Pattern Recognition and Machine Learning it is the best book for you. This book deals with tough topics like basic linear algebra, multivariate calculus, and data science. It is a great book to hammer Pattern Recognition into your brain.

It gives detailed practice exercises that provide a comprehensive introduction to statistical pattern recognition techniques. The book leverages graphic models in a unique way of describing probability distributions. However, it’s not mandatory some experience will hasten the learning process.

  • Paperback: 738 pages
  • Publisher: Springer; 1st ed. 2006. Corr. 2nd printing 2011 edition (15 February 2010)
  • Language: English

Fundamentals of Machine Learning for Predictive Data Analytics

If you understood ML basics and want to know about predictive data analytics this is the best book to go with. Machine Learning can be used to create predictive models by extracting patterns from data sets. You will have both theoretical concepts and practical applications covered in this book.

It describes four approaches to Machine Learning namely similarity-based learning, information-based learning, probability-based learning, and error-based learning. Each of them deals with a non-technical conceptual explanation followed by mathematical models and explanations.

  • Paperback: 624 pages
  • Publisher: MIT Press; 1 edition (4 September 2015)
  • Language: English

Machine Learning: The Art and Science of Algorithms that Make Sense of Data (1st Edition)

If you are somewhere between Intermediate/ Expert Level in Machine Learning and want basics approach this can be great for you. It does justice to the richness and complexity of Machine Learning without losing the unifying principles.

This book has various case studies with increasing complexity along with examples and illustrations. You can see a wide range of logical, geometric and statistical models covered along with new topics like matrix factorization and ROC analysis.

Publisher: Cambridge English (2015)
Language: English

Programming Collective Intelligence: Building Smart Web 2.0 Applications

It is one of the best books to understand Machine Learning. This book by Toby Segaran was written way back in 2007. Data Science and Machine Learning reached its present status of top career avenues. It is less of an introduction to Machine Learning and more of a guide for implementing ML.

It includes topics on creating effective ML algorithms to gather data from applications, create programs to access data from websites and infer the gathered data. Each chapter contains exercises that extend stated algorithms and improve efficiency and effectiveness.

  • Paperback: 360 pages
  • Publisher: O′Reilly; 1 edition (4 September 2007)
  • Language: English


Hope the knowledge shed regarding Machine Learning Books made your choice easy based on the level of expertise. If you have any other queries feel free to reach us and we will help you out at the earliest possible. Stay connected to our site for more updates on Books, Study Materials and Exam Preparation Related Stuff.

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