Stock Closing Price Prediction Using Multiple Linear Regression

This project is a machine learning program designed to predict the closing price of a stock using multiple linear regression.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License
• Contact

Introduction

Stock price prediction is a common application of machine learning. This project uses a multiple linear regression model to predict the closing price of a stock based on various features.

Features

• Predict stock closing prices using multiple linear regression.
• Visualize the relationship between different features and the closing price.
• Evaluate model performance with metrics like RMSE and R².

Installation

1. Clone the repository:

   git clone https://github.com/Vedant2005goyal/stock-price-prediction.git
   cd stock-price-prediction
   

Usage

1.	Ensure you have the necessary data in the correct format. You can modify the data.csv file or use your own dataset.
2.	Run the script to train the model and make predictions:

##Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1.	Fork the repository.
2.	Create your feature branch (git checkout -b feature/AmazingFeature).
3.	Commit your changes (git commit -m 'Add some AmazingFeature').
4.	Push to the branch (git push origin feature/AmazingFeature).
5.	Open a Pull Request.

license

This project is an open source project.

Contact

If you have any questions or suggestions, feel free to contact me at [goyalvedant2005@gmail.com].