ML_Inside_Out
This repo contains Jupyter notebooks which explains how each algorithms behaves intuitively with gifs and images.
If it is a classification algorithm then how it behaves with different shapes of data(like circular or elipsical etc..,). You can change the data set and play with it..
If It is a regression algorithm., then we can see how it optimises function with each epochs.
Best part of all.., It is all written in Python in Jupyter-Ipython notebooks. You can easily play with the code with different datasets or your own dataset..
It is best for small datasets with few hundred points.. Otherwise it might take longer time , as this is not as efficient as sklearn code..