The Tesla Stock Price Prediction project is designed to forecast the future stock prices of Tesla Inc. using historical market data. It includes a comprehensive workflow starting from data preprocessing, exploratory data analysis, and model training using machine learning techniques. The project leverages a dataset (TSLA.csv) containing historical stock prices, and the data is meticulously processed and scaled before feeding it into a regression model to predict the stock's closing prices. The trained model is serialized and saved as Tesla_Stock_Prediction_model.joblib for easy deployment. This project not only demonstrates the application of machine learning in financial markets but also provides a practical framework for training and evaluating predictive models. so it begins