Stock-market-prediction

A Python project for predicting stock market prices using linear regression. This project includes data preprocessing, model training, evaluation, and visualization.

License

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

Stock Market Price Prediction using Linear Regression

This project preprocesses historical stock market data and builds a linear regression model to predict future prices. The model is evaluated using Mean Squared Error (MSE) and visualized with a scatter plot comparing actual vs. predicted prices.

Table of Contents

• Introduction
• Installation
• Usage
• Data Description
• Model Evaluation
• Visualization
• Contributing
• License
• Contact

Introduction

This project demonstrates how to use linear regression to predict stock market prices. It includes data preprocessing steps, model training, evaluation, and visualization of results.

Installation

To run this project, you need Python and the following libraries:

• pandas
• numpy
• scikit-learn
• matplotlib

You can install the required libraries using pip:

pip install pandas numpy scikit-learn matplotlib
# Stock Market Price Prediction using Linear Regression

This project preprocesses historical stock market data and builds a linear regression model to predict future prices. The model is evaluated using Mean Squared Error (MSE) and visualized with a scatter plot comparing actual vs. predicted prices.

## Table of Contents

- [Introduction](#introduction)
- [Installation](#installation)
- [Usage](#usage)
- [Data Description](#data-description)
- [Model Evaluation](#model-evaluation)
- [Visualization](#visualization)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)

## Introduction

This project demonstrates how to use linear regression to predict stock market prices. It includes data preprocessing steps, model training, evaluation, and visualization of results.

## Installation

To run this project, you need Python and the following libraries:
- pandas
- numpy
- scikit-learn
- matplotlib

You can install the required libraries using pip:

```bash
pip install pandas numpy scikit-learn matplotlib
Replace `[[email protected]]` with your actual contact email.

### Detailed Steps to Update Your README.md

1. **Navigate to Your Repository on GitHub:**
   - Go to [GitHub](https://github.com/) and log in.
   - Navigate to your repository, e.g., `https://github.com/Colinmiles/stock-market-prediction`.

2. **Open README.md:**
   - In your repository, locate the `README.md` file.
   - Click on the `README.md` file to open it.

3. **Edit the File:**
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4. **Update the Content:**
   - Add the `## Contact` section at the end of the file. Here's a sample:

```markdown
## Contact

If you have any questions or suggestions, please feel free to contact me at [[email protected]].