Numerical Example: Training a Neural Network Using Vectors and Matrices скачать в хорошем качестве

Numerical Example: Training a Neural Network Using Vectors and Matrices

In this lecture, we work through a complete numerical example of training a neural network using vectors and matrices rather than scalar equations. The network has two nonlinear inputs, three neurons, and a single output, allowing the full matrix–vector structure to be shown clearly. We compute the forward pass, evaluate the error, and apply gradient descent to update weight matrices and vectors. The process is carried out for two iterations so the learning behaviour can be observed step by step. This example shows how the abstract matrix equations translate into concrete numerical updates and how the error decreases as training progresses.