soorgeon VS mlrun

Compare soorgeon vs mlrun and see what are their differences.

soorgeon

Convert monolithic Jupyter notebooks πŸ“™ into maintainable Ploomber pipelines. πŸ“Š (by ploomber)

mlrun

MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications. (by mlrun)
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soorgeon mlrun
3 3
76 1,323
- 2.2%
4.0 9.9
4 months ago 5 days ago
Python Python
Apache License 2.0 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.

soorgeon

Posts with mentions or reviews of soorgeon. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-01.

mlrun

Posts with mentions or reviews of mlrun. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-28.

What are some alternatives?

When comparing soorgeon and mlrun you can also consider the following projects:

ploomber - The fastest ⚑️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️

feast - The Open Source Feature Store for Machine Learning

polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

dagster-example-pipeline - Template Dagster repo using poetry and a single Docker container; works well with CICD

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

nbsnapshot - Automated Jupyter notebook testing. πŸ“™

SmartSim - SmartSim Infrastructure Library.

dagster - An orchestration platform for the development, production, and observation of data assets.

phidata - Build AI Assistants with memory, knowledge and tools.

mosec - A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine