https://github.com/online-ml/beaver

🦫 MLOps for (online) machine learning
https://github.com/online-ml/beaver

Last synced: about 2 hours ago
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🦫 MLOps for (online) machine learning

• Host: GitHub
• URL: https://github.com/online-ml/beaver
• Owner: online-ml
• License: bsd-3-clause
• Created: 2022-03-16T10:45:10.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-03-25T03:20:38.000Z (8 months ago)
• Last Synced: 2024-10-30T05:26:24.646Z (14 days ago)
• Language: Python
• Homepage:
• Size: 6.04 MB
• Stars: 80
• Watchers: 5
• Forks: 13
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Citation: CITATION.cff

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README

        
🦫 Beaver • MLOps for (online) machine learning






























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Beaver is...

✔ [*The whole package*](https://www.youtube.com/watch?v=nzFTmJnIakk&list=PLIU25-FciwNaz5PqWPiHmPCMOFYoEsJ8c&index=5) • 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](https://www.ethanrosenthal.com/2022/05/10/database-bundling/) and define models in Python.

✔ [*Interfaces all the way down*](https://vadosware.io/post/building-an-interface-with-one-implementation-is-unquestionably-right/) • you can plug in your existing message broker, stream processor, model store, etc. This is called a [hexagonal architecture](https://www.wikiwand.com/en/Hexagonal_architecture_(software)) in software design.

✔ *Batteries included* • default infrastructure and monitoring are provided if needed.

## 🤱 Getting started

There is a [pre-built image](https://ghcr.io/online-ml/beaver) you can pull and run 🐳

```sh

docker pull ghcr.io/online-ml/beaver:latest

docker run ghcr.io/online-ml/beaver

```

You can also build the provided [`docker-compose.yaml`](docker-compose.yaml) yourself:

```sh

git clone [email protected]:online-ml/beaver.git

cd beaver

docker-compose up

```

Go to [http://localhost:8501](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

- [🚕 Taxis](examples/taxis)

- [🌳 Batch gradient boosting vs. random forest](examples/batch-trees)

## 📝 License

Beaver is free and open-source software licensed under the [3-clause BSD license](LICENSE).