https://github.com/satyamtripathi8/handwritten_digit_classifier

Explore this repository for a CNN-based handwritten digit classification project. Utilizes TensorFlow/Keras to train and evaluate models, providing a practical example of deep learning in image recognition.
https://github.com/satyamtripathi8/handwritten_digit_classifier

cnn-for-visual-recognition cnn-keras mnist pillow scikit-learn tensorflow

Last synced: over 1 year ago
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Explore this repository for a CNN-based handwritten digit classification project. Utilizes TensorFlow/Keras to train and evaluate models, providing a practical example of deep learning in image recognition.

• Host: GitHub
• URL: https://github.com/satyamtripathi8/handwritten_digit_classifier
• Owner: satyamtripathi8
• Created: 2023-10-17T17:25:08.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-18T13:35:47.000Z (over 2 years ago)
• Last Synced: 2024-01-28T23:09:01.605Z (over 2 years ago)
• Topics: cnn-for-visual-recognition, cnn-keras, mnist, pillow, scikit-learn, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 5.66 MB
• Stars: 4
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Handwritten Digit Classification with Convolutional Neural Networks

This project implements a Convolutional Neural Network (CNN) to classify handwritten digits (0 to 9) using the popular MNIST dataset. The CNN architecture is built using TensorFlow/Keras and achieves accurate digit recognition through a series of convolutional and pooling layers.

## Features

- **Data Loading:** Utilizes Pandas to load handwritten digit data from CSV files.

- **Data Preprocessing:** Reshapes and normalizes the data, preparing it for CNN input.

- **Convolutional Neural Network (CNN):** Implements a CNN model using TensorFlow/Keras layers.

- **Model Training:** Trains the CNN model on the MNIST dataset for handwritten digit recognition.

- **Model Evaluation:** Evaluates the trained model's accuracy on a validation dataset.

- **Prediction:** Provides a function to make predictions on new handwritten digit images.

## Requirements

- Python 3.x

- Pandas

- TensorFlow/Keras

- scikit-learn

## Project Structure

- **`main.py`**: Main Python file containing the code for data loading, preprocessing, model creation, training, evaluation, and prediction.

- **`data/`**: Directory containing the CSV files with the training and testing data.

- **`models/`**: Directory to store saved trained models.

## Acknowledgements

- **MNIST Dataset:** The MNIST dataset used in this project is publicly available and widely used for handwritten digit recognition tasks. More information can be found [here](http://yann.lecun.com/exdb/mnist/).