example-get-started VS metaflow

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

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example-get-started metaflow
2 24
167 7,494
1.2% 2.0%
0.0 9.2
about 1 month ago about 18 hours 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.

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.

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.

What are some alternatives?

When comparing example-get-started and metaflow 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.