kedro-great
metaflow
kedro-great | metaflow | |
---|---|---|
1 | 1 | |
52 | 6 | |
- | - | |
0.0 | 8.2 | |
over 1 year ago | 28 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.
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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.
kedro-great
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
I expected Great Expectations library to be recommended, but nobody told anything. Instead, unit testing and/or smoke tests using pytest. And checking them with Jenkins. Anyway, if Kedro ends up being our project template, I'll keep an eye on the plugin with Great Expectations.
metaflow
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
There are community Forks supporting Kubernetes and KFP. But they are not yet a part of the main framework and support is fluctuating. I think support should be available in the future.
What are some alternatives?
great_expectations - Always know what to expect from your data.
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
Poetry - Python packaging and dependency management made easy
feast - Feature Store for Machine Learning
streamlit - Streamlit — A faster way to build and share data apps.
metaflow-on-kubernetes-docs - Documentation For Running Metaflow on Kubernetes
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution