Stock Prediction App

This repository contains a Python script to predict the closing price of Apple stock using Linear Regression. The script uses data from a CSV file AAPL.csv to train a linear regression model and then predicts the closing price for the test data.

Table of Contents

• Prerequisites
• Installation
• Usage
• Contributing
• License

Prerequisites

• Python 3.x
• Pandas
• NumPy
• Matplotlib
• Scikit-learn

Installation

1. Clone this repository to your local machine using

   git clone https://github.com/Shriansh2002/Stock-Prediction.git

2. Install the required packages using

   pip install -r requirements.txt

Usage

• Put your AAPL.csv file in the same directory as the script.
• Run the script using python apple_stock_prediction.py.
• The script will train a linear regression model on the training data and predict the - closing price for the test data.
• The root mean squared error (RMSE) of the prediction will be displayed on the console.
• A plot will also be displayed showing the predicted closing prices and the actual closing prices.

Contributing

• Fork this repository to your own GitHub account and then clone it to your local device.
• Create a new branch:

  git checkout -b my-new-feature

• Make changes and test them.
• Submit a pull request detailing the changes made and any additional information about the feature.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.