Understanding the SGD optimization from scratch

In this program, we train a single-layer neural network to classify the Iris dataset using Stochastic Gradient Descent (SGD) from scratch.

In this code, we demonstrate a step-by-step process of using Stochastic Gradient Descent (SGD) to optimize the loss function of a single-layer neural network. Additionally, we build the neural network from scratch, providing a clear understanding of its inner workings and implementation.