Deep Learning
A subset of machine learning that uses layered structures called neural networks, loosely inspired by a simplified model of how neurons connect, to find complex patterns in large amounts of data. Deep learning at scale is the technique behind most of the last decade's major AI breakthroughs, including image recognition, speech transcription, and language generation.
Defined in 2 GAGE programs, which carry 2 distinct definitions of it. The wording above is taught in The AI Lobbyist: Certified AI Policy Strategist.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A subset of machine learning that uses layered structures called neural networks, loosely inspired by a simplified model of how neurons connect, to find complex patterns in large amounts of data. Deep learning at scale is the technique behind most of the last decade's major AI breakthroughs, including image recognition, speech transcription, and language generation.
A subset of ML using multi-layered neural networks to process complex, unstructured data such as images, audio, and text.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- What is AI? Definitions, History, and Types · AI Fundamentals, Certified AI Practitioner: Workplace Foundations
- What AI Really Is: No Hype, No Myths, No Fear · Foundations of AI for Lobbyists, The AI Lobbyist: Certified AI Policy Strategist
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.