Project

Neural Network From Scratch

Tools used

Python
NumPy
Machine Learning
Neural Networks
Linear Algebra

Designed and implemented a multi-layer perceptron (MLP) from first principles using only NumPy.

Project brief

Built a fully connected multi-layer perceptron entirely from scratch using NumPy, without relying on machine learning frameworks such as TensorFlow or PyTorch. Implemented forward propagation, backpropagation, gradient descent optimisation, activation functions and weight updates to train the network on classification tasks. The project demonstrates a deep understanding of the mathematical foundations behind neural networks and modern machine learning.