Stock Price Prediction

This project aims to predict stock prices using machine learning algorithms. The goal is to provide accurate predictions based on historical data.

Table of Contents

• Introduction
• Installation
• Usage
• Running the Streamlit App
• Contributing
• License

Introduction

Stock price prediction is a challenging task that involves analyzing historical data to forecast future prices. This project utilizes various machine learning techniques to achieve this goal.

Installation

To get started with the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/yourusername/stock_price_prediction.git

2. Navigate to the project directory:

   cd stock_price_prediction

3. Install the required dependencies:

   pip install -r requirements.txt

Usage

To use the project, follow these steps:

1. Prepare your dataset and place it in the data directory.
2. Run the analysis notebook:

   jupyter notebook analysis.ipynb

Running the Streamlit App

To run the Streamlit app, follow these steps:

1. Ensure you have Streamlit installed (it is included in the requirements).
2. Run the Streamlit app:

   streamlit run app.py

Contributing

Contributions are welcome!

License

This project is licensed under the MIT License.