In plain English
Deep learning is a subset of machine learning that uses neural networks with many layers to learn complex patterns from large amounts of data. Each layer transforms the data a little, so early layers might pick up simple features and later layers combine them into more abstract ones. This layered approach powers most of the recent breakthroughs in language, vision, and generative AI.
Why it matters
Almost every system people now call AI, from chat assistants to image generators, is built on deep learning. Knowing the term connects a lot of otherwise separate tools.
A worked example
In image recognition, the first layers of a deep network detect edges, later layers combine edges into shapes, and the final layers recognise whole objects like a face.
Common confusion
The 'deep' in deep learning refers to the number of layers in the network, not to deep thinking or understanding.