AI Glossary Term

What does “Deep Learning” mean?

Definition

A subset of machine learning that uses many-layer neural networks for representation learning.

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How Deep Learning works

Example

A deep network that recognizes cats learns edges in its first layers, then fur and ear shapes, and finally whole faces in later layers. No one programs those steps; the layers form them during training on many labeled photos.

Why it matters

Deep learning drives most current progress in speech recognition, image analysis, and language models. It needs a lot of data and compute, which shapes who can build such systems.

Common questions

What makes learning 'deep'?

The network has many stacked layers, each building on the output of the one before.

Is deep learning the same as AI?

No. It is a subset of machine learning, which is itself a part of AI.

When is deep learning not the best choice?

On small tabular datasets, simpler methods such as gradient-boosted trees often match or beat it and are cheaper to run.

TransformerA neural architecture that uses attention to model relationships across sequences in parallel.AGI (Artificial General Intelligence)A hypothetical AI system that can perform most intellectual tasks at a human level across many domains.AnnotationHuman-added labels or metadata used to train or evaluate machine learning models.Convolutional Neural Network (CNN)A neural architecture optimized for processing grid-like data such as images.EmbeddingA numeric vector representation that captures semantic meaning of text, images, or other data.Foundation ModelA large pre-trained model that can be adapted to many downstream tasks.

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