Introduction

Our brain is really good at identifying and recognizing things. We want the machines to be able to do the same. A neural network is a framework that is modeled after the human brain to simulate our learning processes. Neural networks are designed to learn from data and recognize the underlying patterns. As with all learning algorithms, neural networks deal with numbers. Therefore, if we want to achieve any real world task involving images, text, sensors, and so on, we have to convert them into the numerical form before we feed them into a neural network. We can use a neural network for classification, clustering, generation, and many other related tasks.

A neural network consists of layers of neurons. These neurons are modeled after the biological neurons in the human brain. Each layer is basically a set of independent neurons that are connected to the neurons the adjacent layers. The input layer corresponds to the input data that we provide, and the output layer consists...