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HandDigit Classifier

Overview

HandDigit Classifier is a Python project that classifies handwritten digits from the MNIST dataset using a custom neural network.
It focuses on data preprocessing, feature extraction, and normalization to improve model accuracy.

Features

  • Neural network built from scratch in Python
  • Trains and evaluates using the MNIST dataset
  • Data analysis and visualization using Matplotlib
  • Preprocessing with NumPy and Pandas

Technologies Used

  • Python
  • NumPy
  • Pandas
  • SciPy
  • Matplotlib
  • OpenCV

How to Run

  1. Download or clone this repository.

  2. Open the project folder in your terminal or IDE.

  3. Make sure you have the required Python libraries installed:

    pip install numpy pandas scipy matplotlib opencv-python

  4. Run the classifier:

    python handdigit_classifier.py

Dataset

Uses the MNIST dataset of handwritten digits (0–9). You can download it from: http://yann.lecun.com/exdb/mnist/

Author

Rudronha Rana Python Developer | Machine Learning Enthusiast