Deep Learning

Deep Learning is a core method of machine learning — an AI technology that organizes neural structures in multiple layers. The 'deep' refers to the many layers of artificial neurons, which function like a multi-story building of understanding: each level extracts more abstract features than the one below it. While the first layer detects simple edges in images, the final layer identifies complete faces or medical anomalies. Training proceeds in two steps: backpropagation propagates the error backward through all layers, computing gradients via the chain rule — that is, how strongly each weight contributes to the error. The actual adjustment of the weights is then handled by an optimization method such as gradient descent (e.g., SGD or Adam), which uses those gradients. Deep learning has substantially changed computer vision, speech recognition, and text generation. From CNNs for image analysis to RNNs for sequential data to Transformers for language models — this family of architectures forms the backbone of modern AI systems.