This project implements an SVM classifier from scratch to classify MNIST handwritten digits (0-9) without using any SVM libraries. Key features include:
Support for Linear, Polynomial, and RBF kernels One-vs-Rest strategy for multi-class classification Hyperparameter tuning with cross-validation Evaluation using accuracy, confusion matrix, and F1-score Visualization of misclassified digits and kernel performance comparison