-> 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