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Delta🌊🔀

DeltaMLOps is an innovative tool designed for the efficient deployment and management of online machine learning models, specifically tailored for integration with the River library. It utilizes a microservice architecture, allowing for dynamic and scalable operations in machine learning workflows.

Features 🚀

  • Microservice-Based: Each ML model functions as an independent microservice.
  • Dual API System: Includes a public API for training and inference, and a management API for configuration and monitoring.
  • Dynamic Model Configuration: Easily configurable models at runtime, adaptable to changing data streams.
  • Containerized Deployment: Utilizes Docker for consistent and easy deployment, with Kubernetes support for scaling.

Getting Started

Prerequisites

  • Docker
  • Python 3.8+
  • River 0.21.0

Installation

Quickstart

# Quickstart guide with code snippets

Usage

# Example usage code

Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/yourFeature)
  3. Commit your Changes (git commit -m 'Add some Feature')
  4. Push to the Branch (git push origin feature/yourFeature)
  5. Open a Pull Request

License

Distributed under the BSD License. See LICENSE for more information.

Contact

Sebastian Wette - [email protected]