A data-driven project predicting used car prices through EDA and a Linear Regression model. Insights revealed strong effects of year, mileage, and engine size on price. Achieving an R² of 0.83, the study highlights how adding categorical features can further refine predictions and boost model performance.

Used Car Price Prediction using Machine Learning includes Data Cleaning, Data Preprocessing, 8 Different ML Models and Some Insights from Data

Dive into polynomial regression and its assumptions in car price prediction. This repo explores Linear, Polynomial, Ridge, Lasso, and Elastic-Net models on the CarDekho dataset for accurate estimates. A deep dive into regression and regularization.

The Car Price Prediction Model uses machine learning to predict the selling price of a car based on features like model, year, kilometers driven, fuel type, seller type, transmission, and more. Built using Python's scikit-learn and a Linear Regression model, it provides accurate predictions based on historical car data.

Machine learning model with linear regression for car price prediction

A multiple linear regression model for the prediction of car prices.

Car Price Prediction with Machine Learning The price of a car depends on a lot of factors like the goodwill of the brand of the car, features of the car, horsepower and the mileage it gives and many more. Car price prediction is one of the major research areas in machine learning. So if you want to learn how to train a car price prediction model then this article is for you. In this article, I will take you through how to train a car price prediction model with machine learning using Python.

Building a Machine Learning Model to Predict the Price of the Car By Comparing Performance of Different Regression Techniques (Simple Linear Regression, Multiple Linear Regression, Polynomial Regression)

This repository contains a project of Old / Used Cars Price Prediction Model using Machine Learning and Data Analysis.

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The goal of this project is to build multiple linear regression models for the prediction of car prices.

A Prediction Model of Used Car Price

Car Price Prediction using Linear Regression and OneHotEncoding for categorical features to estimate selling price based on multiple car attributes.

🚗 A professional FastAPI-based REST API that predicts car prices using a Gradient Boosting machine learning model. Simply provide a car brand, and the API returns an intelligent price prediction along with the closest matching vehicle from a real user database.

Developing an accurate car price prediction model to aid buyers and sellers, with a user-friendly interface, continuous improvement, and ethical considerations, for informed decisions in the automotive market.

🚗 Estimate used car prices in Tunisia using a Multiple Linear Regression model trained on 60,000+ synthetic listings (23 brands, 89% accuracy). Interactive Streamlit app with real-time predictions.

A UI create for car price prediction model to predict the model and this UI is not working with backend ML code

This project focuses on exploratory data analysis (EDA) and machine learning for car price prediction. It includes data cleaning, feature engineering, visualization, and regression models to understand the key factors that influence car prices and build accurate predictive models.

Used car price prediction using various machine learning models like Linear Regression, Decision Tree Regressor, and Random Forest Regressor with data preprocessing, feature engineering, and evaluation.

Used car price prediction tool was created for classifieds websites such as Craig’s list. Helps the seller set a price point using the Logistical Linear Regression model, helping the buyer and the seller.

A Regression based ML model for prediction of car prices in market

Car_price_prediction_model

The Car Price Prediction project uses machine learning techniques to predict the selling price of used cars based on various features such as make, model, year, mileage, condition, and more

This Python script is designed to predict the selling price of cars using a Decision Tree Regressor model.

It is a python machine learning model that predicts the price of a second hand car using different models like linear regression, random forest, gradient boosting, SVM It also uses libraries like pandas, numpy, matplotlib, seaborn to import datasets, plot graphs, remove outliers and clean the dataset for training and testing the model for better accuracy

Car Price Prediction using Machine Learning Models

This project is about prediction selling price of used car using machine learning model and flask web application

Car Price Prediction using Random Forest Regression model

Machine learning model with linear regression for car price prediction

This app is a web-based tool for predicting the price of used cars. It uses a machine learning model trained on a dataset of used car listings to make predictions. Users can input information about a used car (e.g., make, model, year, mileage, etc.) and the app will display the predicted price of the car. The app is built using Flask and incorpor