The project involved extensive data cleaning,feature engineering,exploratorydata analysis (EDA), Collected and preprocessed a dataset ofused carsusing Pandas and NumPy,handling missing values, duplicates, and categorical variables.Using skewness and kurtosis,OutliersDetection by using IQR method, Trained and evaluated multiple regression models

Theprojectinvolvedextensivedatacleaning,featureengineering,exploratorydata analysis (EDA)

Used Cars Price Prediction A simple ML project using linear regression and scikit-learn pipelines to predict used car prices, with a Flask web app for user interaction.

Car Price Prediction | ML Project Predicts the selling price of used cars using a Linear Regression model. 🔹 Key Features: ✔️ Data preprocessing & feature encoding ✔️ Feature scaling & model training ✔️ Performance evaluation (RMSE, R², MAE) ✔️ User input function for real-time predictions 📌 Tech Stack: Python, Scikit-Learn, Pandas, Matplotlib