Repository to host basic notes and simple implementations of common methods related to Statistical Learning.

It will host implementations on both Python and R, but focusing on Python. Expect the R code to be really disordered and not that user friendly.

To set up and environment with the python dependencies to run the Python code, I recommend using/configuring pipenv. And once that tool is installed you can run the following in the repository root directory:

pipenv install
pipenv shell

This will create a Python virtual environment with all the dependencies (beware that it may take a while to create it) and give you a shell inside that virtual environment.

There will be notebooks depicting some basic examples on fundamentals of Statistical Learning elements.

• about_flexibility.ipynb: Shows the effect of sample size and flexibility in a model/prediction.