Machine Learning glossary
A neutral KnowledgeAtlas glossary reference for Machine Learning.
How to use this glossary
This glossary introduces working vocabulary used in machine learning. Definitions are intentionally concise and should be read with the linked full articles, where context, trade-offs, and limitations are explained.
Architecture
In machine learning, architecture describes a structured way to organize responsibilities and relationships. The exact meaning depends on the system boundary and the people using it.
Asset
In machine learning, asset describes an element used within a wider technical or creative process. The exact meaning depends on the system boundary and the people using it.
Boundary
In machine learning, boundary describes a reviewable stage or rule that helps teams coordinate work. The exact meaning depends on the system boundary and the people using it.
Component
In machine learning, component describes a structured way to organize responsibilities and relationships. The exact meaning depends on the system boundary and the people using it.
Dependency
In machine learning, dependency describes an element used within a wider technical or creative process. The exact meaning depends on the system boundary and the people using it.
Framework
In machine learning, framework describes a reviewable stage or rule that helps teams coordinate work. The exact meaning depends on the system boundary and the people using it.
Interface
In machine learning, interface describes a structured way to organize responsibilities and relationships. The exact meaning depends on the system boundary and the people using it.
Iteration
In machine learning, iteration describes an element used within a wider technical or creative process. The exact meaning depends on the system boundary and the people using it.
Lifecycle
In machine learning, lifecycle describes a reviewable stage or rule that helps teams coordinate work. The exact meaning depends on the system boundary and the people using it.
Model
In machine learning, model describes a structured way to organize responsibilities and relationships. The exact meaning depends on the system boundary and the people using it.
Pipeline
In machine learning, pipeline describes an element used within a wider technical or creative process. The exact meaning depends on the system boundary and the people using it.
Protocol
In machine learning, protocol describes a reviewable stage or rule that helps teams coordinate work. The exact meaning depends on the system boundary and the people using it.
Repository
In machine learning, repository describes a structured way to organize responsibilities and relationships. The exact meaning depends on the system boundary and the people using it.
Runtime
In machine learning, runtime describes an element used within a wider technical or creative process. The exact meaning depends on the system boundary and the people using it.
Validation
In machine learning, validation describes a reviewable stage or rule that helps teams coordinate work. The exact meaning depends on the system boundary and the people using it.
Related articles
Demo reference entry for layout testing only. No invented publication is presented as a source.