Digit Recognizer

A pipeline that classifies handwritten digit images (MNIST) using PCA for dimensionality reduction and supervised classifiers (Decision Tree, SVM).

Python 3 Jupyter Notebook pandas NumPy scikit-learn matplotlib
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Project Overview

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 .

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Project Details

  • Completion Date February 2024
  • Category Machine Learning
  • Project Type HTML File

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Digit Recognizer