This repository provides bare-bones implementations of machine learning models and algorithms, written in Python using only NumPy and SciPy. It covers supervised learning (regression, classification, SVM), unsupervised learning (clustering, dimensionality reduction, RBM), reinforcement learning (Q-learning, policy gradients), and deep learning (CNNs, autoencoders). The goal is to make the inner workings of these algorithms transparent and accessible rather than optimized for production use.