tensaeb/hktm-vehicle-price-predictor

A Streamlit app for predicting vehicle prices in Ethiopian Birr and US Dollars. Uses machine Learning model trained on a dataset of vehicle sales # HKTM Vehicle Price Predictor ## GROUP MEMBERS: Hermella Lemma GSE/4034/16 Kalkidan Kassahun GSE/9049/16 Mignote Deresse GSE/3444/16 Tensae Befikadu GSE/7621/16 Bereket Tamirat GSR/0935/16 ## Power Point Presentation docs.google.com This repository contains a Streamlit application for predicting vehicle prices in Ethiopian Birr (ETB) and US Dollars (USD). It uses a machine learning model trained on a dataset of vehicle sales. ## Automate car Price from telegram channel Colab Code colab.research.google.com ## Vehicle Price Predictor Colab Code colab.research.google.com ##Deployed Website for the predictor hktm-vehicle-price-predicto… ## Overview The application allows users to select various car features (Make, Model, Year, Fuel, Transmission, Condition) and then predicts the price range of the vehicle in ETB and USD. The predicted prices are categorized into ranges of 100,000 ETB and $1000 USD for better readability. ## Key Features - **Dynamic Exchange Rate:** Fetches the latest ETB to USD exchange rate from an external API. - **Interactive UI:** Uses Streamlit select boxes for easy input of car features. - **Price Prediction:** Uses a trained machine learning model to predict the vehicle price. - **Price Categorization:** Groups predicted prices into ranges of 100,000 ETB and $1000 USD. - **Clear Output:** Displays the exchange rate, predicted price ranges, and model accuracy. ## Repository Structure hktm-vehicle-price-predictor/ ├── app.py # Streamlit application code ├── VehicleData2.csv # Dataset used for training (can be replaced) ├── vehicle_price_model.joblib # Trained machine learning model ├── preprocessor.joblib # Trained preprocessing model └── README.md # This documentation ## Setup and Usage ### Prerequis …