Apppublic

AbdulMoiz25/MNIST-NaiveBayes-AbdulMoiz

sourceHugging Faceupdated 11mo agoView on Hugging Face

0likes

App README

MNIST Digit Classifier (Naïve Bayes)

![Gradio](https://www.gradio.app) ![Python](https://www.python.org/) ![Hugging Face](https://huggingface.co/spaces) ![Model](https://scikit-learn.org/stable/modules/naive_bayes.html)

Deployed on Hugging Face Spaces by Abdul Moiz Meer

Live Demo

Check the live app here: MNIST‑NaiveBayes‑AbdulMoiz

🎯 App Description

—Upload an image of a handwritten digit (0–9).
—The app predicts the digit using a Naïve Bayes classifier trained on the MNIST dataset.
—Responsive, modern UI with smooth gradients, hover effects, and polished cards.

🧠 Model Details

—Model Type: Naïve Bayes (MultinomialNB / BernoulliNB / GaussianNB / ComplementNB)
—Dataset: MNIST (70,000 handwritten digit images, 28×28 pixels)
—Best Model: Saved as best_mnist_model.pkl and integrated into the app.

🚀 Deployment

—Hosted on Hugging Face Spaces using Gradio SDK.
—Supports responsive layouts and modern styling.
—Simply upload the project files to a new Space to deploy instantly.

🧑‍💻 Author

Developed by Abdul Moiz Meer