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Overview

Conceptual Overview

With Vessl, machine learning researchers can run experiments and deploy models on Kubernetes clusters without any background in 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
Last modified 16d ago
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