Free and Open Machine Learning Book


This book is all about applying open machine learning solutions for real practical use cases. So the core focus is on how outlining how you can apply machine learning in a simple way. Books with lots of mathematical background information on how machine learning works are available for more than 70 years. So if you are keen on mathematical background information, you should take a look at the open learning resources section of this application.

Machine learning is an exciting powerful technology. The use of machine learning technology on larger scale opens new opportunities and will give improvements for everyone. Machine learning technology should be available for everyone. So without barriers. But with the rise of new machine learning enabled products it is important to be able to ask critical questions on how safety, security, privacy and ethical issues are handled.

This book is created to give you a head start to use and apply new Open Source machine learning technologies to solve your business problems. Important machine learning concepts are explained, but the main emphasis is on providing insights in the possibilities that are now available within the growing open source machine learning ecosystem. This so you can start applying machine learning in your business today. And be able to judge answers regarding important quality aspects, like safety, security and privacy.

This book gives an overview of all important OSS machine learning frameworks and OSS support tools that you can use for prototyping with machine learning or when using machine learning for real production use cases.


This document is in alfa-stage!! Collaboration is fun, so Help Us by contributing ! There are some chapters currently written and editing work (typos,spelling) is yet to be done! Some more background information of the project can be found in the readme on And do not forget to join the ROI movement!


Table of Contents



The following people have contributed to the Free and Open Machine Learning project:

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If you wish to make comments regarding this document, please raise them as GitHub issues. Or send comments by email if you are unable to raise issues on GitHub. All comments are welcome!