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Lightning AI for Cutting-Edge Deep Learning Models in Stock Markets

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alphadl - Lightning AI for Cutting-Edge Deep Learning Models in Stock Markets

alphadl leverages Lightning AI to implement and compare various deep learning models for stock market prediction.

Models

  • StockMixer: A simple yet powerful MLP-based architecture for stock price forecasting.

Data Interface

  • OpenBB: Utilized for accessing comprehensive stock market data.

Features

  • Efficient and Scalable: Utilizes Lightning AI for streamlined deep learning workflows.
  • Advanced Prediction Models: Implements state-of-the-art ML/DL models for stock market forecasting.
  • Data Integration: Seamlessly integrates OpenBB for data acquisition.
  • Configuration Management: Employs Hydra for flexible configuration management.
  • Experiment Tracking: Integrates Weights & Biases (wandb) for tracking and visualizing experiments.

Installation

  1. Clone the Repository:

    git clone https://github.com/yourusername/alphadl.git
    cd alphadl
  2. Install Required Packages:

    pip install -e .

How to Execute

Run the training script with a specified experiment configuration:

python src/train experiment=<experiment_name>

For example:

python src/train experiment=stockmixer_sp500_1d

Contributions

We welcome contributions to alphadl! Here's how you can get involved:

  1. Fork the Repository: Create a new branch for your feature or bug fix.
  2. Code Style: Follow existing code style and formatting conventions.
  3. Testing: Write unit tests to ensure your changes work as expected.
  4. Submit a Pull Request: Provide a clear description of your changes.

We appreciate all contributions, whether it's a bug fix, new feature, or documentation improvement. If you're unsure where to start, reach out on our issue tracker or discussion forum.

License

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

Contact

For questions or feedback, please contact us at [email protected].

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Lightning AI for Cutting-Edge Deep Learning Models in Stock Markets

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