Core Concepts#
Note
Kolena Workflows are simplified in Kolena Datasets. If you are setting up your Kolena environments for the first time, please refer to Kolena Datasets.
In this section, we'll get acquainted with the core concepts on Kolena, and learn in-depth about the various features
offered. For a brief introduction, see the Quickstart Guide or the
Building a Workflow tutorial. For code-level API documentation, see the
API Reference Documentation for the kolena
Python client.
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Testing in Kolena is broken down by the type of ML problem you're solving, called a workflow. Any ML problem that can be tested can be modeled as a workflow in Kolena.
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Test cases and test suites are used to organize test data in Kolena.
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In Kolena, a model is a deterministic transformation from test samples to inferences.