cascade
polyaxon
cascade | polyaxon | |
---|---|---|
9 | 9 | |
16 | 3,486 | |
- | 0.5% | |
9.3 | 8.7 | |
5 days ago | 15 days ago | |
Python | Python | |
Apache License 2.0 | 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.
cascade
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modeldb VS cascade - a user suggested alternative
2 projects | 12 Dec 2023
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Sacred VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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keepsake VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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aim VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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guildai VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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metaflow VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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clearml VS cascade - a user suggested alternative
2 projects | 5 Dec 2023
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
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Announcing Cascade
This is Cascade - very lightweight MLE solution for individuals and small teams
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 itβs 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?
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
MLflow - Open source platform for the machine learning lifecycle
NVTabular - NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
kubeflow - Machine Learning Toolkit for Kubernetes
powershap - A power-full Shapley feature selection method.
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
zenml - ZenML π: Build portable, production-ready MLOps pipelines. https://zenml.io.
dvc - π¦ ML Experiments and Data Management with Git
ds2 - Easiest way to use AI models without coding (Web UI & API support)
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.
FeatureHub - The most comprehensive library of AI/ML features across multiple domains. Our goal is to create a dataset that serves as a valuable resource for researchers and data scientists worldwide
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]