Machine Learning theory and applications using Octave or Python.

Machine Learning: Statistical Learning

In this section, you can learn about the theory of Machine Learning and applying the theories using Octave or Python. Octave (open-source version of Matlab) is useful for rapid prototyping before mapping the code to Python.

This introduction is derived from Machine Learning, a course taught by Andrew Ng from Stanford University. There are other introductions such as Data School and Udacity’s Machine Learning Nanodegree.

I would like to give full credits to the respective authors as these are my personal python notebooks taken from deep learning courses from Andrew Ng, Data School and Udemy :) This is a simple python notebook hosted generously through Github Pages that is on my main personal notes repository on They are meant for my personal review but I have open-source my repository of personal notes as a lot of people found it useful.