unionml
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unionml | rubicon-ml | |
---|---|---|
6 | 1 | |
330 | 123 | |
1.2% | 2.4% | |
4.0 | 8.0 | |
6 months ago | 1 day ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
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unionml
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Who needs MLflow when you have SQLite?
Checkout Flyte.org and itβs sibling project https://www.union.ai/unionml
- UnionML: the easiest way to build and deploy machine learning microservices
- GitHub - unionai-oss/unionml: UnionML: the easiest way to build and deploy machine learning microservices
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Show HN: UnionML β a Python framework for building ML microservices
Hi HN!
Niels here. I'm the creator of *UnionML*, a Python MLOps framework that removes the boilerplate and friction associated with building and deploying machine learning systems to production.
I've been training and deploying models for almost a decade now, and one pain-point I've consistently had is managing the complexity of building and maintaining an ML stack that works for the entire model development lifecycle - from prototyping to production.
UnionML is built on top of Flyte (https://www.flyte.org) and exposes a functional interface for defining the building blocks of your ML application via decorators -- think Flask or FastAPI method endpoints -- and UnionML takes care of bundling them into microservices for different use cases such as:
- model training
- batch prediction
- online prediction
- (more coming soon!)
This project aims to unify the rich ecosystem of data, ML, and MLOps tools that have emerged over the last decade or so (e.g. MLFlow, Sagemaker, Spark, etc.) to provide a nice UX for model developers, in both individual and team settings.
It's very early days for this project, so if you're interested in getting involved or learning more, you can go to the:
- Docs: https://unionml.readthedocs.io/en/latest/
- Repo: https://github.com/unionai-oss/unionml
- Slack: https://flyte-org.slack.com/archives/C03JL38L65V
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What are some alternatives?
ploomber-engine - A toolbox π§° for Jupyter notebooks π: testing, experiment tracking, debugging, profiling, and more!
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
neptune-client - π The MLOps stack component for experiment tracking