Deep Learning

Deep learning is a subfield of machine learning that uses neural networks with many layers to learn patterns directly from raw data. The term "deep" refers to the number of layers, which can range from a dozen to several hundred. Each layer applies a simple mathematical transformation to its input and passes the result forward. Through repeated exposure to examples, the network adjusts how each layer operates, gradually producing more accurate outputs. No hand-crafted features are needed. The network figures out what matters on its own. Deep learning is behind most AI breakthroughs of the past decade. Speech recognition systems that convert spoken words to text, image search engines that label photographs, recommendation engines that suggest videos, all run on deep networks. These models capture relationships that traditional algorithms miss entirely. Beyond consumer products, deep learning drives medical imaging tools that spot tumors with higher precision than many human radiologists, autonomous vehicles that interpret road conditions in real time, and climate models that analyze satellite data to improve forecasting. As hardware gets faster and datasets get larger, deep learning keeps expanding what machines can solve.