As data scientists, machine learning is a required skill for our job. The material is easy to find online to learn Machine Learning as many people have developed the material for others to understand. However, it is tricky to find the one that covers everything a beginner needs.

To help everyone find suitable learning material, I want to present my top Machine Learning GitHub book project in this article. Let’s get into it.

1. mlcompendium

The mlcompendium GitBook project is an open-source project initiated by Ori Cohen. The project is intended to curate all the machine learning education material in one place, which they did pretty well. If we try to count, more than 500 topics have been added to the mlcompendium GitBook project.

The compendium consists of informative articles, links, papers, courses, etc. It could take a long time to read all the compendium material, so I suggest you take your time.

The learning material is written well and perfect for beginners and professionals alike. For example, the contents in the Data Science section are concise yet cover many concepts that everyone should know about data science.

You could find almost every piece of information required for your machine learning — Data Science Tools, statistics, Calculus, NLP, Evaluation Metrics, and many more. Every material you need for your learning is available.

Some content might take you to another link or course, but they are still good content for your learning. Overall, mlcompendium is an excellent reference for anyone learning machine learning.

If you want to contribute to this compendium, don’t hesitate to contact the author.

2. Ruiterpan

Ruiterpan or Rui Pan’s blog is a GitBook project initiated by Rui Pan to curate a machine learning paper. It is precisely to host his reading paper and various blogs regarding machine learning and operating system.

I know that many people are not used to reading papers and need a lesson. Luckily, the Ruiterpan GitBook project compiles a lesson to learn how to read an academic paper.

There is also a section within the Ruitepan GitBook project for learning whatever you need to know about life in Computer Science Ph.D. — from applying, what to prepare, and even life after the Ph.D.

In my opinion, Ruiterpan GitBook is perfect for people who love to learn machine learning from an academic perspective and want to apply more experimental data science.

3. Scrapbook

If the Ruitepan GitBook project is focused on the academic perspective, Scrapbook is a project that focuses on learning in a hands-on way. It focuses on preparing yourself as a machine learning engineer because the project is developed by Stephan Osteburg, who is personally a machine learning engineer.

Most of the content within Scrapbook is the basic concepts of data science and the practice you could do. For example, learning projects, code challenges, SQL codes, and many more.

However, some content would prepare you on the employment aspects — interview, job titles, product management, agile approach, and many more.

There are also a lot of external links to the book, courses, and resources on specific projects to help you learn.

I suggest you look at the Scrapbook GitBook if you love a hands-on approach instead of the theory. The content was pretty good for someone who wants to prepare for their machine learning interview and data science employment.

4. Irosyadi

Irosyadi GitBook project isn’t a straightforward machine learning GitBook project; instead, it focuses on their data (and others) applications for us to understand. The Irosyadi GitBook name comes from the author Imron Rosyadi.

In the GIF below, let me show what you could expect in the Irosyadi GitBook project.

As you can see, there is an abundant collection of applications you could select and learn from the Irosyadi GitBook project. Each content would contain various applications, for example, the Jupyter Notebook App.

The content is categorized pretty well. Although, expect to access many external links because the learning comes from various applications listed rather than thoroughly explained within the GitBook.

5. Machine Learning with TensorFlow.js

The name is self-descriptive as this GitBook is dedicated to teaching all you need to know about Machine Learning with TensorFlow.js.

The contents within this GitBook project are divided into four sections, and that is:

JavaScript for Machine Learning
Developing Neural Network Solutions
Deep Learning using TensorFlow.js
Summary and Closing

This GitBook project is good for someone who wants to learn machine learning using TensorFlow in more detail. Some sections are not finished yet, but most learning material is still pretty good for students.

Conclusion

Machine learning is essential for data scientists because it is a tool we use for our work. To help everyone find the suitable learning material, I want to present my top Machine Learning GitHub book project:

mlcompendium
Ruiterpan
Scrapbook
Irosyadi
Machine Learning with Tensorflow.js

I hope it helps!

Learn Machine Learning from top GitBook Projects