Machine Learning Exercises In Python, Part 5

This post is part of a series covering the exercises from Andrew Ng's machine learning class on Coursera. The original code, exercise text, and data files for this post are available here. In part four we wrapped up our implementation of logistic regression by extending our solution to handle multi-class classification and testing it on the hand-written digits data set. Using just logistic regression we were able to hit a classification accuracy of about 97.5%, which is reasonably good but pretty much maxes out what we can achieve with a linear model. In this blog post we'll again tackle the hand-written digits data set, but this time using a feed-forward neural network with backpropagation.