Uber Rides Prediction Flask

Overview

A modern Flask web application that predicts weekly Uber rides based on user inputs. The application features an Uber-inspired design theme and uses a scikit-learn machine learning model for predictions. Built with production-ready setup and deployed on Railway for public access.

Challenge

Ride demand varies with pricing, population, income, and parking cost. The task was to model weekly ride volume from these few inputs and deliver the prediction through an easy-to-use app.

Solution

scikit-learn regression model served by a production Flask/Gunicorn app on Railway.

Architecture

scikit-learn regression · Flask + Gunicorn · Bootstrap UI · Railway deploy

Results

• Model Type: Regression
• Deployment: Railway
• Framework: scikit-learn
• Production-ready Flask application
• Uber-inspired modern UI design
• Real-time ride prediction
• Deployed on Railway platform
• Scalable architecture with Gunicorn

Technologies

• Python
• Flask
• scikit-learn
• Gunicorn
• Railway
• Bootstrap