StockSavvy

StockSavvy is an advanced stock prediction system that utilizes TensorFlow and reinforcement learning techniques to forecast stock prices. This project integrates with the yfinance library to fetch historical stock data and includes a Django app that can be seamlessly added to existing Django projects.

Features

• Reinforcement Learning Model: Implements reinforcement learning algorithms for stock price prediction.
• TensorFlow Integration: Utilizes TensorFlow for building and training neural networks.
• Stock Data Retrieval: Fetches historical and real-time stock data using the yfinance library.
• Django Integration: Provides a Django app that integrates with existing Django projects for easy deployment and management.

Libraries and Tools Used

• TensorFlow: For constructing and training reinforcement learning models.
• yfinance: To obtain stock market data.
• NumPy: For numerical computations and data manipulation.
• Pandas: For data processing and analysis.
• Matplotlib: For plotting and visualizing data.
• Scikit-learn: for additional machine learning tools.
• Django: For web framework integration.

Setup and Installation

1. Clone the Repository:

   git clone https://github.com/garbhitsh/StockSavvy.git
   cd StockSavvy

2. Create and Activate a Virtual Environment:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install Required Packages:

   pip install -r requirements.txt

4. Setup Google Cloud Vision (if applicable):

   • Follow the Google Cloud Vision documentation to set up authentication and obtain your API key.

   • Set up the environment variable for authentication:

     export GOOGLE_APPLICATION_CREDENTIALS="path/to/your/credentials.json"

5. Run the Django App (if integrating):

   python manage.py runserver

Django Integration:

• Add the StockSavvy app to your Django project’s INSTALLED_APPS in settings.py:

  INSTALLED_APPS = [
      # Other apps
      'stock_savvy',
  ]

• Include the app’s URLs in your project’s urls.py:

  from django.urls import path, include
  
  urlpatterns = [
      path('stock/', include('stock_savvy.urls')),
  ]

• Configure any required settings in your Django project’s settings.py file.

Configuration

• Configuration File: Update the config.json file with paths, settings, and API keys as needed.
• Environment Variables: Ensure any required environment variables (e.g., API keys) are properly set if applicable.

Contributing

Contributions are welcome! If you have suggestions, improvements, or issues, please open an issue or submit a pull request. Make sure your contributions align with the project’s guidelines.

License

This project is licensed under the MIT License.