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:
Allocate machine resource according to the needs of the Project.
Import project source code from GitHub.
Upload a dataset from local disk or cloud vendors.
Run experiments and use Sweep to find the optimal hyperparameter.