This repository contains implementations of machine learning concepts from scratch using only numpy. It covers fundamental topics including neural network architecture, backpropagation, and weighted sums, alongside more advanced topics like transformers and distributed model training. The project serves as a learning resource for understanding how ML systems work internally without relying on deep learning frameworks.