Smoothing out the overfitting.py code
Fixed colors
Refactoring network2.py, and added new option for weight initialization
First draft of program to contrast results between different approaches to weight initialization
Comparative weight initialization now working pretty well
Results for weight initialization comparison experiment
Minor improvements
Minor fixes
Getting the overfitting graphs right (earlier versions weren't initializing the weights correctly)
Make the number of epochs to train for a parameter
Modified overfitting.py to make it easier to run on varied data sets
Adding results for overfitting on full data set (much less is going on), plus a new graph
Results for the regularized network trained on the full data set
Adding a plot to show how more data improves training accuracy
Adding figure of an MNIST digit and its rotated version
Adding log plot showing what happens when more training data is used
Added fudge factor which improves the appearance of the rotated MNIST 5
Added comparison graph for SVMs running over many training set sizes
Removing old code
Regenerating graphs for 1/sqrt weight initialization