praveenliyanage/airline-delay-prediction

A project leveraging machine learning to forecast airline delays. Features a user-friendly Flask web interface for inputting flight details and receiving delay predictions.

Airline-Delay-Prediction

Airline Delay Prediction with Flask Web Application

Overview

This project aims to predict airline delays using machine learning techniques and provides a user-friendly web interface for users to interact with the prediction model. The machine learning model is built using historical flight data, and the Flask web application allows users to input flight details and receive predictions on potential delays.

Features

• Machine Learning Model: Utilizes a trained machine learning model to predict airline delays based on historical flight data.
• Flask Web Application: Provides a user interface to input flight details and receive delay predictions.
• Interactive Dashboard: Visualizes predictions and insights about delays, enhancing user experience.

Project Structure

• app/: Contains the Flask web application code.
• data/: Holds the dataset or links to the dataset used for training the machine learning model.
• models/: Stores the trained machine learning model(s).
• notebooks/: Jupyter notebooks used for data exploration, model training, etc.
• utils/: Utility scripts or modules.

Getting Started

1. Clone the Repository:

   git clone https://github.com/PraveenLiyanage/Airline-Delay-Prediction.git
   cd Airline-Delay-Prediction
   

Install Dependencies:

pip install -r requirements.txt