## Ml Related Resource
1. https://github.com/trekhleb/homemade-machine-learning
There are two folders homemade and notebook, homemade contains all well commented low level code and doc explaining maths. Notebook is like a more of API use.
1. https://github.com/Avik-Jain/100-Days-Of-ML-Code
It contains more pictorial explanation with just API usage, worth seeing, might come in handy to revise quickly
1. https://github.com/rushter/MLAlgorithms
This contains fundamental implementation of bit more advanced algorithms.
## How I found all of these repo
1. https://github.com/topics/machine-learning-algorithms
I went there and scrolled, you can do that too
## If this isn't helpful 
1. If this is not helpful, you can search for "implement {x , x=(linear, logistic regression, svm, decision tree)}", follow a few article by hand, if you don't get a feel of how to implement it from the first article.
2. If you have done all of the above step, maybe take some random data, try to remember the the theory, and implement it yourself, it will help