Simple Hand-Written Digit Classifier

A simple hand-written digit classifier which can classify digits with 98% accuracy.

You can visit the website to try this yourself.

Project components

Dataset

• We are using the MNIST dataset to train and test our model to recognise digits.
• You can view the dataset here.

Model

• A dense neural network with architecture:

• Trained on the MNIST dataset for 60 epochs using back propagation.

UI

• A website made using Vue js to test and showcase the classification prowess of the model.
• You can visit the website.

To build this on your computer

1. cd to where you want the project to live.
   • Create a virtual environment and activate it. optional
2. To set up the project, run these commands:
   ```
   git clone “git@github.com:Varun487/WrittenDigitClassifier.git”

cd WrittenDigitClassifier

pip install -r requirements.txt

3. To run the jupyter notebook:

jupter notebook

4. To build the UI:

npm run build
```

Credits

This project is inspired by a medium article by Carlos Aguayo.