Car-prices-prediction-

The code processes a dataset of car information, performing data cleaning and preprocessing. Categorical features like car name, company, and fuel type are one-hot encoded, and the data is visualized using seaborn and matplotlib. A Linear Regression model from scikit-learn is trained to predict car prices based on features like the car's name, company, year, kilometers driven, and fuel type. The model's performance is evaluated, and the trained model is serialized to a file for future use. The script also demonstrates how to use the model to make price predictions for new car data. In summary, it's a comprehensive data preprocessing and machine learning pipeline for predicting car prices based on various attributes.