Stochastic Gradient Descent

The best way to see the notebook (without cloning this repo and running locally) is at https://nbviewer.jupyter.org/github/dtnewman/gradient_descent/blob/master/stochastic_gradient_descent.ipynb. If you click on the .ipynb file above, github will show it rendered as HTML, but doesn't properly render all the formulas.

This IPython notebook gives a tutorial for implementing gradient descent and stochastic gradient descent in Python. This work is based on the algorithm described by Andrew Ng in Stanford CS 229 course. See http://cs229.stanford.edu/ for more info.