This repository implements common machine learning algorithms from scratch in Python 3.x, including gradient descent variants, linear regression, and logistic regression. The primary motivation is educational—to understand the math and intuition behind why these algorithms work on different datasets. Visualizations show the training process in both 2D and 3D, including effects of momentum. Scikit-learn is used only for accessing datasets and scalers, while core algorithms are implemented without ML framework dependencies.