Machine Learning Handbook¶
This site provides theorical explanations and Python-based demonstrations for various Machine Learning concepts, techniques and tools. Associated practical challenges (katas) can be found here.
Its content is inspired by a large number of sources, from which numerous ideas and several illustrations were borrowed (more details here).
The content of this site is designed to be browsed thematically rather than sequentially.
From any chapter, you can launch a live session in the cloud by pressing the button in the toolbar above and selecting a hosted runtime environment. You will be able to test the code and regenerate the chapter output.