How to set-up a Jupyter Notebook or R-Studio IDE to import or write your program code including Kubeflow pipeline DSL. Learn about the supported ML frameworks or custom image import into your notebook.
The next generation of enterprise applications will increasingly be AI/ML models applied to accelerate existing processes or solve new problems such as accelerating drug discovery and development in life sciences. Kubeflow is an open source reference architecture for AI/ML platform initiated by Google and contributed by several IT platform infrastructure leaders in the industry such as IBM, Redhat, Cisco, Dell, AWS for on-prem and hybrid deployment of AI/ML.
Cloud-based computing has enabled organizations to make use of high-performance resources without requiring large IT groups. And it has enabled a supply of production-ready applications to companies who might not otherwise be able to access them. But, what if your organization can’t make use of the public cloud?