A major contributor to this article appears to have a close connection with its subject.(September 2022) |
Original author(s) | |
---|---|
Developer(s) | Kubeflow Contributors[1] - AWS, Bloomberg, Google, IBM, NVIDIA, Nutanix, Red Hat, Arrikto, and others |
Initial release | April 5, 2018 | [2]
Stable release | 1.8[3]
/ November 1, 2023 |
Repository | github |
Written in | Go, Python |
Platform | Kubernetes |
Type | Machine Learning Platform |
License | Apache License 2.0 |
Website | kubeflow |
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google. The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development (Kubeflow Notebooks[4]), model training (Kubeflow Pipelines,[5] Kubeflow Training Operator[6]), model serving (KServe[a][7]), and automated machine learning (Katib[8]).
Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component.[9]
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