Coursera Machine Learning

This repository contains python implementations of certain exercises from the course by Andrew Ng.

For a number of assignments in the course you are instructed to create complete, stand-alone Octave/MATLAB implementations of certain algorithms (Linear and Logistic Regression for example). The rest of the assignments depend on additional code provided by the course authors. For most of the code in this repository I have instead used existing Python implementations like Scikit-learn.

How it works :

You need jupyter in order to run / edit these exercices.
You can install it with python package manager with the command pip install jupyter
Then in directory notebooks simply type jupyter notebook

Dependencies :

Python packages : pandas numpy matplotlib seaborn scikit-learn

References:

Course main page is here
Forked from here
Python tutorial forked from here
SciPy tutorial forked from here