Now that we understand the basics of a neural network, we can define Deep Learning. In simple terms:Deep Learning is a subfield of machine learning that uses neural networks with many hidden layers.That’s it. The “deep” in deep learning refers to the depth of the network—the number of hidden layers it has. While a simple neural network might have one hidden layer, a deep neural network can have dozens, hundreds, or even thousands.
Adding more layers fundamentally changes what a network can learn. It allows the model to learn patterns in a hierarchical way, building complex concepts out of simpler ones.Imagine a network trying to identify a cat in an image.
A “Shallow” Network (1 hidden layer): This network would have to learn to go directly from raw pixel data to the concept of a “cat” all in one step. This is incredibly difficult and requires the layer to learn very complex patterns simultaneously.
A “Deep” Network (many hidden layers): This network can break the problem down into a series of steps, with each layer specializing in a different level of abstraction.
Hidden Layer 1: Might learn to recognize very simple patterns, like edges, corners, and color gradients from the pixels.
Hidden Layer 2: Combines the edges and corners from the previous layer to learn more complex shapes, like circles, ovals, and pointy triangles.
Hidden Layer 3: Combines those shapes to learn to recognize parts of a cat, like eyes, ears, and whiskers.
Subsequent Layers: Continue combining these features until the final layers can assemble the learned parts into the high-level concept of a “cat.”
This hierarchical feature learning is precisely why deep learning excels at tasks involving complex, unstructured data like images, audio, and text. The real world is layered and hierarchical, and deep networks are structured in a way that can effectively model that complexity. They automatically learn the relevant features from the data, which is a massive advantage over older machine learning techniques that often required an expert to manually engineer features.
