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.
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).
- Python 3.x
- scikit-learn
- pandas
- numpy
- matplotlib
- Clone this repository.
- Install the required packages listed in
requirements.txt. - Open the Jupyter Notebook provided and run the cells to replicate the experiments.
Feel free to modify this README as needed for your project!