I made a neural network to classify fake animals || Devlog

The process of how I made a really basic neural network to classify two different species based on their width and height. The neural network I made is a basic perceptron which takes in two input values and tells you whether the species is 0 or 1. It uses the sigmoid activation function, begins with two randomized weights and a bias, and is written in Python in the Sublime text editor. This video aims to provide a basic overview of how a neural network is made. More advanced neural networks typically include many more inputs and also has hidden layers, which are not included here.