Overview

Conceptual Overview

With VESSL, machine learning researchers can run experiments and deploy models on Kubernetes clusters without any background in software engineering or DevOps. A typical workflow on VESSL is composed of 5 steps:

  1. Allocate machine resource according to the needs of the Project.

  2. Import project source code from GitHub.

  3. Upload a dataset from local disk or cloud vendors.

  4. Run experiments and use Sweep to find the optimal hyperparameter.

  5. Deploy models into production as REST APIs.

VESSL Resources
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