Step-by-step guide to build a simple neural network in PyTorch from scratch

PyTorch is one of the most used libraries for building deep learning models, especially neural network-based models. In many tasks related to deep learning, we find the use of PyTorch because of its features and capabilities like production-ready, distributed training, robust ecosystem, and cloud support. In this article, we will learn how we can build a simple neural network using the PyTorch library in just a few steps. For this purpose, we will demonstrate a hands-on implementation where we will build a simple neural network for a classification problem.  We will accomplish this implementation in the following steps:- Step 1: Creating the dataStep 2: Loading the data using data loaderStep 3: Building a neural network model Defining the neural net classInstantiating the classifierStep 4: Training the neural network modelOptimizing loss curveDefining decision boundariesStep 5: Making Predictions Let’s start with the first step, where we will create a dataset for i