omegaml
runhouse
| omegaml | runhouse | |
|---|---|---|
| 2 | 6 | |
| 94 | 711 | |
| - | 2.4% | |
| 8.1 | 9.8 | |
| 2 days ago | 2 days ago | |
| Python | Python | |
| Apache License 2.0 | 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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omegaml
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What are some open-source ML pipeline managers that are easy to use?
May I add, https://github.com/omegaml/omegaml
- Who uses Apache Airflow for MLOps? Enlighten me.
runhouse
- Runhouse
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Better GPU Cluster Scheduling with Runhouse
With Runhouse, it’s easy to send code to your compute no matter where it lives, and efficiently utilize your resources across multiple callers scheduling jobs (e.g. researchers, pipelines, inference services, etc). We believe less is more when it comes to AI DevOps, so we don’t make any assumptions about the structure of your code or the infrastructure to which you’re sending it.
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The Great MLOps Hoax: Is It Just Data Engineering in Disguise?
You may want to look at run.house [0] for a pretty powerful solution to many of these problems.
[0] https://github.com/run-house/runhouse
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Who uses Apache Airflow for MLOps? Enlighten me.
I was the product lead for PyTorch and was seeing the same problem all over, so I've been working on a new tool for exactly this: https://github.com/run-house/runhouse
- Run-house/runhouse: Programmable remote compute and data across environments
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How easy is it to migrate from one MLOps tool to another? And what SaaS platform would you recommend?
I've been working on a very flexible and low-lift OSS ML platform that sounds like it would suit your needs: https://github.com/run-house/runhouse
What are some alternatives?
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
srez - Image super-resolution through deep learning
MLflow - Open source platform for the machine learning lifecycle
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Metrics - Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
pdpipe - Easy pipelines for pandas DataFrames.
gensim - Topic Modelling for Humans
PyBrain
scikit-learn - scikit-learn: machine learning in Python
Pylearn2 - Warning: This project does not have any current developer. See bellow.