hyper-ml/hyperML
Frictionless Machine Learning on Kubernetes
This tool helps data scientists and ML engineers run their machine learning experiments and code more easily using cloud resources. You can launch or schedule Jupyter notebooks and Python jobs directly from your IDE, leveraging shared infrastructure. It handles the underlying technical complexities, allowing you to focus on the science, not the setup.
No commits in the last 6 months.
Use this if you are a data scientist or ML engineer who wants to run computationally intensive machine learning tasks using cloud infrastructure without leaving your familiar development environment.
Not ideal if you do not work with machine learning models or do not require scalable cloud resources for your computational tasks.
Stars
15
Forks
1
Language
Go
License
Apache-2.0
Category
Last pushed
Mar 07, 2023
Commits (30d)
0
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