This repository is focused on providing educational material to those who start learning Machine Learning with python. [Many things I learn myself as I provide material for education, therefore the repository is of an altruistic character; have fun learning new things!]
Most of the information is provided in the form of .ipynb files, so you could experiment with information yourself or see specifically what outputs some certain functions provide before they become a part of a big all-in-one function. As well, such files also try to explain as much as possible about the process of building one or another function.
For a note - this repositrory does not follow any books, it's just something I personally at one point or another decide to experiment and learn about and feel it's worth while to share. Besides, it helps me learn the material better too! As well, that's the motivation I want to promote - self-starting interest that is not sparked when you are put into the position when you need to learn something for ML, but when you want to learn something (and it does not have to be something big, just something enjoyable, that is more than enough for starters).
If this helps anyone, I'm more than satisfied!