Awesome
<h1>🦫 Beaver • MLOps for (online) machine learning</h1> <p> <!-- Tests --> <a href="https://github.com/online-ml/beaver/actions/workflows/unit-tests.yml"> <img src="https://github.com/online-ml/beaver/actions/workflows/unit-tests.yml/badge.svg" alt="tests"> </a> <!-- Code quality --> <a href="https://github.com/online-ml/beaver/actions/workflows/code-quality.yml"> <img src="https://github.com/online-ml/beaver/actions/workflows/code-quality.yml/badge.svg" alt="code_quality"> </a> <!-- Mypy --> <a href="http://mypy-lang.org/"> <img src="http://www.mypy-lang.org/static/mypy_badge.svg" alt="mypy"> </a> <!-- License --> <a href="https://opensource.org/licenses/BSD-3-Clause"> <img src="https://img.shields.io/badge/License-BSD%203--Clause-blue.svg?style=flat-square" alt="bsd_3_license"> </a> </p>Beaver is...
✔ The whole package • it's a framework to develop, deploy, and maintain machine learning models. And that includes feature engineering.
✔ No fuss • there's an SDK to do stuff, and a UI to see stuff.
✔ Online-first • it is designed for online machine learning models, while also supporting batch models.
✔ Opinionated • it encourages you to process data with SQL and define models in Python.
✔ Interfaces all the way down • you can plug in your existing message broker, stream processor, model store, etc. This is called a hexagonal architecture in software design.
✔ Batteries included • default infrastructure and monitoring are provided if needed.
🤱 Getting started
There is a pre-built image you can pull and run 🐳
docker pull ghcr.io/online-ml/beaver:latest
docker run ghcr.io/online-ml/beaver
You can also build the provided docker-compose.yaml yourself:
git clone git@github.com:online-ml/beaver.git
cd beaver
docker-compose up
Go to http://localhost:8501 to access the user interface.
This is all you need to run Beaver. Check out the examples to see how to use it.
👀 Examples
📝 License
Beaver is free and open-source software licensed under the 3-clause BSD license.