metaflow VS example-get-started

Compare metaflow vs example-get-started and see what are their differences.

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metaflow example-get-started
24 2
7,494 167
2.3% 1.2%
9.2 0.0
1 day ago about 1 month ago
Python Python
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

metaflow

Posts with mentions or reviews of metaflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-05.

example-get-started

Posts with mentions or reviews of example-get-started. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-27.

What are some alternatives?

When comparing metaflow and example-get-started you can also consider the following projects:

flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.

zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]

kedro-great - The easiest way to integrate Kedro and Great Expectations

clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

great_expectations - Always know what to expect from your data.

dvc - 🦉 ML Experiments and Data Management with Git

feast - Feature Store for Machine Learning

Poetry - Python packaging and dependency management made easy

fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production

awesome-mlops - A curated list of references for MLOps

aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.