Guide to Feed-Forward Network using Pytorch with MNIST Dataset

Neural Networks are a series of algorithms that imitate the operations of a human brain to understand the relationships present in vast amounts of data. Each “neuron” present in a neural network can be defined as a mathematical function that collects and classifies information according to the specific architecture. The network, in general, comprises interconnected nodes, known as perceptrons. A multi-layered perceptron, or MLP, consists of perceptrons arranged in interconnected layers. The input layer collects input patterns. The output layer has classifications or output signals to which input patterns are mapped.  WHAT IS A FEED-FORWARD NEURAL NETWORK? A feed-forward neural network is a classification algorithm that consists of a large number of perceptrons, organized in laye