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