Based on Andrew Ng's Deep Learning course in Coursera, I have decided to keep track of the functions used whilst implementing DNNs using Numpy, as well as new ones I have used before and plan to use in the future. The plan thus far is, as more and more functions are added, to eventually separate the library into different files to be easier to find the desired functions.

I will not include all the functions used in the course, just those that will help me further understand those used in Tensorflow and Keras.

If all else fails and I do not continue to mantain this collection, I will commit it to Brendan Fortuner's ML Cheatsheet.