https://github.com/gokulnpc/handwritten-digit-classification

This web app is a simple handwritten digit classification model built using a neural network with the MNIST dataset. The MNIST dataset is a collection of 70,000 small square 28x28 pixel grayscale images of handwritten single digits between 0 and 9. The model is built using TensorFlow and Keras, and the web app is built using Streamlit.
https://github.com/gokulnpc/handwritten-digit-classification

classification-model deep-learning neural-networks streamlit

Last synced: about 2 months ago
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This web app is a simple handwritten digit classification model built using a neural network with the MNIST dataset. The MNIST dataset is a collection of 70,000 small square 28x28 pixel grayscale images of handwritten single digits between 0 and 9. The model is built using TensorFlow and Keras, and the web app is built using Streamlit.

• Host: GitHub
• URL: https://github.com/gokulnpc/handwritten-digit-classification
• Owner: gokulnpc
• Created: 2024-03-23T09:56:24.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-03-23T10:16:36.000Z (about 1 year ago)
• Last Synced: 2025-02-02T03:44:52.261Z (4 months ago)
• Topics: classification-model, deep-learning, neural-networks, streamlit
• Language: Jupyter Notebook
• Homepage: https://handwritten-digit-classification-gokulnpc.streamlit.app/
• Size: 1.06 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Handwritten Digit Classification with Neural Networks

This web app is a simple handwritten digit classification model built using a neural network with the MNIST dataset.

The MNIST dataset is a collection of 70,000 small square 28x28 pixel grayscale images of handwritten single digits between 0 and 9.

The model is built using TensorFlow and Keras, and the web app is built using Streamlit.