Handwritten Digit Classification

This repository contains a mini Data Science project for handwritten digit classification using the sklearn.datasets.load_digits dataset, where various classification algorithms (KNN, SVM, Decision Tree, Random Forest, and MLPClassifier) are compared using cross-validation.

Overview

The project involves data preprocessing, model training, evaluation using metrics like accuracy and confusion matrix, and hyperparameter optimization to determine the best-performing model for classifying digits (0-9).

Requirements

• Python 3.x
• scikit-learn
• pandas
• numpy
• matplotlib

How to Run

1. Clone this repository.
2. Install the required packages listed in requirements.txt.
3. Open the Jupyter Notebook provided and run the cells to replicate the experiments.

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Feel free to modify this README as needed for your project!