/ml-back-propagation

Implementation of the machine learning back propagation algorithm from the ground up, without the use of any learning libraries.

Primary LanguagePython

ml-back-propagation

This is an object-oriented implementation of the back propogation algorithm for machine learning from the grounds up (only pre-installed python libraries have been used).

This implementation is only for a single hidden layer, but variable number of neurons in that layer. This is because in practice, this algorithm does not work for a deep network due to the vanishing gradient problem.

Steps to run

The program needs to be given the number of hidden layer neurons as a command line argument.

Run using Python 2.7. Since it does not require any external package, there is no requirements.txt.

Steps to run:

$ python learn.py 12