Data science algorithm implementation

To brush up my knowledge of popular data science algs, and pick up my lost math mind after university, I set myself a goal to implement those algs in raw python+numpy/numba implementation.
The main purpose is to understand how those models work, any considerations during fitting, loss function choice, so that hopefully I can apply those knowledge in my day-to-day work.
Also wouldn't object any fun trying to improve the running speed by using numba :)\

To do list:

• Logistic Regression
• Linear Regression
• K-means
• KNN
• SVM
• Backpropagation NN ...