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A pipeline that classifies handwritten digit images (MNIST) using PCA for dimensionality reduction and supervised classifiers (Decision Tree, SVM).
<div>The project loads the MNIST training set with pandas, applies PCA to preserve 95% of variance, then fits both a Decision Tree and an SVM (with hyperparameter tuning via GridSearchCV). Final evaluation reports an overall accuracy of 85% along with per-class precision, recall, and F1-scores .</div><div><br></div>
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