The kaos ML platform is fully functional when initialized with a running endpoint (see below). See Deploying Infrastructure for instructions on generating a running endpoint.
kaos init -e <running_endpoint>
This step is mandatory to ensure the end user (i.e. Data Scientists) is connected to kaos. Initialization can be thought of as the "glue" binding the backend and the command line interface (CLI). Once again, the following conceptual overview indicates how
kaos init connects the end user the entire kaos backend.
The kaos CLI consists of the following top-level commands.
Initialize the kaos environment
Retrieves templates for getting started
Organize and separate ML working environments
Deploy hosted notebooks for experimentation and building ML models
Create training jobs for training ML models with ready-made and split features
Deploy an endpoint with a trained model
Usage and sub-level commands are further detailed when running
--help. For example, retrieving the
mnist template for usage involves the following command:
kaos template get --name mnist
The same conceptual overview is presented once again to highlight their "interaction" with the kaos backend.