Teme Tehnici de Optimizare (TO), Anul 3, Semestrul 2, Facultatea de Matematica si Informatica, Universitatea din Bucuresti

Python implementations of Support Vector Machines (Soft Margin) and Linear Regression (Univariate/Multivariate) from scratch using NumPy and Gradient Descent. Includes performance comparison with Scikit-Learn on the German Credit dataset.

This repository provides a Python implementation of Support Vector Machines (SVM) from scratch using a quadratic solver like CXPY. The implementation includes both soft margin and hard margin SVM algorithms.