tiff-wang/mnist-demo-flask-app

MNIST - Handwritten Digit Recognition Applications

The goal of this project is to demonstrate a simple example of how to integrate a machine learning model into a real-life application. In order to do so, this repository holds the source code for a flask application integrated with a feature to predict whether a student will pass or fail a course given a specific set of inputs.

This project is to be used for introductory workshops aimed at teaching the basics of integrating ML into a Flask App.

Prerequisites

Install necessary python packages

pip install -r requirements.txt

Train the model

Run python -m model.model from the root directory.

After training the model, the trained weights and the optimizers are saved in

├── model
|    ├── results
|           ├── model.pth
|           ├── optimizer.pth

Running the Flask Application

Run the app.py file from the root directory.

python app.py

Go to localhost:5000 to access the application from the browser of your choice.