Machine learning is an application of artificial intelligence that gives a system an ability to automatically learn and improve from experiences without being explicitly programmed. In this article, we have listed some of the best free machine learning books that you should consider going through (no order in particular).

**Author:** Jure Leskovec, Anand Rajaraman, Jeff Ullman

Based on the Stanford Computer Science course CS246 and CS35A, this book is aimed for Computer Science undergraduates, demanding no pre-requisites. This book has been published by Cambridge University Press.

**Author:** Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

This book holds the prologue to statistical learning methods along with a number of R labs included.

**Author:** Ian Goodfellow and Yoshua Bengio and Aaron Courville

This Deep Learning textbook is designed for those in the early stages of Machine Learning and Deep learning in particular. The online version of the book is available now for free.

**Author:** Cam Davidson-Pilon

This book introduces you to the Bayesian methods and probabilistic programming from a computation point of view. The book is basically a godsend for those having a loose grip on mathematics.

**Author:** Shai Shalev-Shwartz and Shai Ben-David

For the mathematics- savvy people, this is one of the most recommended books for understanding the magic behind Machine Learning.

Author: LISA lab, University of Montreal

Deep Learning tutorial using Theano is a must- read if you are willing to enter this field and is absolutely free.

**Author:** Andreas Mueller

Exploring statistical learning, this tutorial explains the use of machine learning techniques with aim of statistical inference. The tutorial can be accessed online for free.

**Author:** Stephen Marsland

This book has a lot to offer to the Engineering and Computer Science students studying Machine Learning and Artificial Intelligence. Published by CRC press and written by Stephen Marsland, this book is unfortunately not free. However, we highly recommend you to invest in this one. Also, all the python code are available online. These code are a great reference source for python learning.

**Author:** Willi Richert and Luis Pedro Coelho

This book is also not available for free but including it serves our list justice. It is an ultimate hands-on guide to get the most of Machine Learning with python.

These are some of the finest machine learning books that we recommend. Have something else in mind? Comment below with your list of some awesome machine learning books.

© 2019 Data Science Central ® Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

**Technical**

- Free Books and Resources for DSC Members
- Learn Machine Learning Coding Basics in a weekend
- New Machine Learning Cheat Sheet | Old one
- Advanced Machine Learning with Basic Excel
- 12 Algorithms Every Data Scientist Should Know
- Hitchhiker's Guide to Data Science, Machine Learning, R, Python
- Visualizations: Comparing Tableau, SPSS, R, Excel, Matlab, JS, Pyth...
- How to Automatically Determine the Number of Clusters in your Data
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- Fast Combinatorial Feature Selection with New Definition of Predict...
- 10 types of regressions. Which one to use?
- 40 Techniques Used by Data Scientists
- 15 Deep Learning Tutorials
- R: a survival guide to data science with R

**Non Technical**

- Advanced Analytic Platforms - Incumbents Fall - Challengers Rise
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- How to Become a Data Scientist - On your own
- 16 analytic disciplines compared to data science
- Six categories of Data Scientists
- 21 data science systems used by Amazon to operate its business
- 24 Uses of Statistical Modeling
- 33 unusual problems that can be solved with data science
- 22 Differences Between Junior and Senior Data Scientists
- Why You Should be a Data Science Generalist - and How to Become One
- Becoming a Billionaire Data Scientist vs Struggling to Get a $100k Job
- Why do people with no experience want to become data scientists?

**Articles from top bloggers**

- Kirk Borne | Stephanie Glen | Vincent Granville
- Ajit Jaokar | Ronald van Loon | Bernard Marr
- Steve Miller | Bill Schmarzo | Bill Vorhies

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives**: 2008-2014 | 2015-2016 | 2017-2019 | Book 1 | Book 2 | More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions

## You need to be a member of Data Science Central to add comments!

Join Data Science Central