pipelines
polyaxon
| pipelines | polyaxon | |
|---|---|---|
| 3 | 9 | |
| 3 | 3,483 | |
| - | 0.4% | |
| 2.7 | 8.7 | |
| 5 months ago | 9 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pipelines
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pipelines - Create Async Processing Pipelines Quick!
Reference for the aggregate\inputs property and usage -) demo.
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pipelines- Create async pipelines quick!
theboxhaan/pipelines
- theboxahaan/pipelines
polyaxon
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Any MLOps platform you use?
If you're not concerned about self-hosting, WandB is one of the more fully featured training monitoring tools (I've used it in the past without any issues but the lack of data and training privacy and lack of self-hosting possibilities makes it a hard no for anything that isn't scholastic). Polyaxon is an alternative but rewriting all your variable logging to conform to their requirements makes it very difficult to switch to it in the middle of a project so you have to commit to it from the get-go.
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[D] Kubernetes for ML - how are y'all doing it?
We use Polyaxon and it’s pretty good
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[D] What MLOps platform do you use, and how helpful are they?
Disclosure - I'm the author of Polyaxon.
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Does anyone have experience with polyaxon?
I just came across https://github.com/polyaxon/polyaxon because mlflow gives me a hard time and costs my company money by the day because it is not working as expected.
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[D] Productionalizing machine learning pipelines for small teams
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
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Top 5 tools to get started with MLOps !
Polyaxon : https://polyaxon.com
- Open source alternative to AWS Sagemaker, Google AI Platform, and Azure ML
What are some alternatives?
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
MLflow - Open source platform for the machine learning lifecycle
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
kubeflow - Machine Learning Toolkit for Kubernetes
pypyr automation task runner - pypyr task-runner cli & api for automation pipelines. Automate anything by combining commands, different scripts in different languages & applications into one pipeline process.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
celery - Distributed Task Queue (development branch)
dvc - 🦉 ML Experiments and Data Management with Git
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
neptune-client - 📘 The MLOps stack component for experiment tracking