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Predict the price of used cars

I'll use various machine learning algorithms to predict the price of used cars.

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.

A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.

To be able to predict used cars market value can help both buyers and sellers. So In this Project, we are going to predict the Price of Used Cars using various features.

🚕 Given a set of features such as the car brand, model, year of manufacture and other factors, we would be able to predict the price of the car in the next few years. We would be using different regression models in our process of predicting the prices of cars respectively.

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🚗 Solving the problem of predicting the price of a used car using Sklearn's supervised machine learning techniques.

A Machine Learning Project that uses Random Forest Regressor model to predict used cars price based on some attributes such as kilometers driven, age, number of previous owners etc.

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Data Science & Machine Learning Internship at Flip Robo Technologies

A model for predicting used car prices in Saudi Arabia

Tesla Car Range, Base Price and Precise Price Prediction - Machine Learning

This is a python project for building a linear regression model that is used to predict used car prices from a given dataset using machine learning. The dataset used for this project is taken from Kaggle. For the complete video explanation, check out the following link.

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End to end implementation and deployment of Machine Learning Car Price Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.

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🚗 Predict car prices instantly with Linear & Lasso Regression! Built with Streamlit, scikit-learn, pandas & matplotlib. Compare models, explore data, and learn ML hands-on. Fast, open source, and easy to use for students & developers!

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

This repo contains all the source code and obtained data for the used cars prices

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Technologies: Nutch 1.6, MapReduce in Java, Mahout. For selling a used car, its price can be predicted by giving some attributes. e.g. Car Model, total miles, engine type. Trained data will be provided to our system to predict the price for new data. Used Nutch to crawl car data from 52 states which is on craigslist.org. Over 0.3 million records were fetched. The content was then pruned using two MapReduce Jobs. The first MapReduce cleaned the data removing unwanted unicode symbols and incomplete data (information without car model or total miles or engine or price). The Second MapReduce extracted the required attributes and emitted in tsv format. This tsv was then provided to a Naïve Based Classifier in Mahout. A classification model was built from the training data. This models predicts the price when attributes like car model model, miles, engine was provided.

ML model to determine price of car based on certain features.

The Car Price Prediction Web App is a Flask-based web application that utilizes machine learning to predict the approximate price of used cars based on various features. The app is designed as a sample project to showcase my skills.

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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.