-> This is a solution to the Softmax Regression exercise in the Stanford UFLDL Tutorial(http://ufldl.stanford.edu/wiki/index.php/Exercise:Softmax_Regression)
-> The code has been written in Python using Scipy and Numpy
-> The code is bound by The MIT License (MIT)

Running the code:

-> Download the gunzip data files and the code file 'softmaxRegression.py'
-> Put them in the same folder, extract the gunzips and run the program by typing in 'python softmaxRegression.py' in the command line
-> You should get an output saying 'Accuracy : 0.9262', it signifies an accuracy of 92.6%
-> The code takes about 5 minutes to execute on an i3 processor