mlrun
fds
Our great sponsors
| mlrun | fds | |
|---|---|---|
| 3 | 3 | |
| 1,294 | 382 | |
| 6.0% | -0.3% | |
| 9.9 | 3.7 | |
| 5 days ago | 4 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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.
mlrun
- Discussion on Need of Feature Stores
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I reviewed 50+ open-source MLOps tools. Here’s the result
You should also add MLRun: https://github.com/mlrun/mlrun
- Has anyone here been able to deploy Mlrun successfully on Kubernetes cluster?
fds
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I reviewed 50+ open-source MLOps tools. Here’s the result
Also fds, it's an open source command line wrapper around Git and DVC.
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Data Science Workflows — Notebook to Production
At DagsHub, we’re integrated with DVC, which I love using. First and foremost, it’s open-source. It provides pipeline capabilities and supports many cloud providers for remote storage. Also, DVC acts as an extension to Git, which allows you to keep using the standard Git flow in your work. If you don’t want to use both tools, I recommend using FDS, an open-source tool that makes version control for machine learning fast & easy. It combines Git and DVC under one roof and takes care of code, data, and model versioning. (Bias alert: DagsHub developed FDS)
- Show HN: FastDS – Open-Source Machine Learning Version Control. Fast and Easy
What are some alternatives?
feast - Feature Store for Machine Learning
PyDrive2 - Google Drive API Python wrapper library. Maintained fork of PyDrive.
dagster-example-pipeline - Template Dagster repo using poetry and a single Docker container; works well with CICD
dvc - 🦉 ML Experiments and Data Management with Git
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
Keras - Deep Learning for humans
SmartSim - SmartSim Infrastructure Library.
scikit-learn - scikit-learn: machine learning in Python
phidata - Build AI Assistants with memory, knowledge and tools.
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
mosec - A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
lakeFS - lakeFS - Data version control for your data lake | Git for data