Introduction: All of us, when start out with neural network, go through pictures of networks, try and understand complex equations; get baffled by the back-propagation equations and take our time to eventually assimilate the knowledge of what all that stands for. Recently while mentoring students for our new effort mentorbruh , one of my students asked some pretty interesting yet very basic questions. This content is an effort to write down those so that it can help other students who are going through neural networks first time and have these doubts. But before that, let's brush up the basics once pretty quickly. Abstract of this article: In this post, we are going to take small steps in explaining what is neural network, what are input,output and hidden layers; how does a node calculate its values. We will also briefly touch the concepts of bias, activation, hidden layer number count and all the related artifacts. In the more looser second part of this neural network b...
I write about machine learning models, python programming, web scraping, statistical tests and other coding or data science related things I find interesting. Read, learn and grow with me!