figo2001 / pipeline-project

Build a predictive accident analysis app by loading historical accident data, preprocessing with Scikit-learn's Pipeline, training a model, and deploying using Streamlit for real-time predictions.

Accident Prediction App

Project Overview

This repository contains the source code for an Accident Prediction App. This application utilizes a machine learning pipeline to predict the likelihood of accidents in given scenarios based on historical data. It's designed to help organizations and safety personnel implement better safety measures by forecasting potential accidents before they occur.

Features

• Data Processing: Clean and prepare historical accident data.
• Model Training: Use a machine learning pipeline to train the prediction model.
• Prediction API: A simple API to receive input data and provide predictions.
• User Interface: A web-based interface using Streamlit for easy interaction with the prediction model.

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.8 or above
• pip (Python package installer)

License

Distributed under the MIT License. See LICENSE for more information.

Screenshot

streamlit-app-2024-04-21-03-04-24.webm