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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. 1.
    Allocate machine resource according to the needs of the Project.
  2. 2.
    Import project source code from GitHub.
  3. 3.
    Upload a dataset from local disk or cloud vendors.
  4. 4.
    Run experiments and use Sweep to find the optimal hyperparameter.
  5. 5.
    Deploy models into production as REST APIs.
VESSL Resources