Flight Delay Prediction ✈️

This repository contains a flight delay prediction application. The application uses a logistic regression model to predict the likelihood of a flight being delayed based on the day of the week and the arrival airport.

Repository Structure 📚

• client/: Contains the frontend code for the application, built with React and Material-UI.
• server/: Contains the backend code for the application, which serves the prediction API.
• data/flights.csv: The dataset used for training the model.
• manage-flight-data.ipynb: A Jupyter notebook that contains the data analysis and model training process.
• server/model.pkl: The trained logistic regression model.

How to Run ⚒️

1. Start the backend server by running the server/server.py script.
2. Start the frontend application by running npm run dev in the client/ directory.

Features 👀

• The application allows users to select a day of the week and an airport, and then predicts whether a flight will be delayed or not.
• The prediction is made by a logistic regression model trained on the flights.csv dataset.

Contributing 📝

Contributions are welcome! Please feel free to submit a pull request.

License 🪪

This project is licensed under the terms of the MIT license. See the LICENSE file for details.