ML examples using sklearn library
The first project is an example from the sklearn diabetes dataset using LinearRegression model. Originally written in jupyter notebook there is a .py file as a seperate viewer
Secndly I implemented Linear Refression from scratch. This is in reference to the Andrew Ng Coursera course. The data used is this example is in the data2.txt file
The stacking_models file is a copy to kaggle kernel https://www.kaggle.com/serigne/stacked-regressions-top-4-on-leaderboard which is a very descriptive and educational kernel. It helped me understand the basics of emsemble learning and feature engineering. Coding the kernel line-by-line by hand really helped me syntactically and experimenting with hyperparameters was an even greater experience.