There is so much work going on #MachineLearning and #DeepLearning space. The basis of most of that is the artificial neural networks. I assume that you understand ANN well and are now trying to implement the same. If you do not understand it yet, then consider going through this blog. In this Blog I am going to implement neural network in python, just to understand their inner workings. This will be a good primer to understanding how Keras / tensorflow or pyTorch allow us to code at much higher level abstracting the internal details and make our lives as deep learning professionals much easier.
There are multiple tutorials available to understand the concepts of Artificial Neural Networks (ANN) and I do not want this blog to again talk about the same things that have been said so many times and in better ways. In this blog I am going to focus on what all points you need to keep in mind when going through ANN concepts so that you understand ANN at much deeper level to be able to code it by hand. Essentially in this blog I am going to highlight some key points that you need to focus on so that you are able to write your own code to implement neural network.