Overview
Neural networks are the foundation of modern AI. They consist of layers of interconnected 'neurons' that process data and learn to recognize patterns through training.
Structure
- Input Layer: Receives the initial data.
- Hidden Layers: Perform complex transformations and feature extraction.
- Output Layer: Produces the final prediction or classification.
Training
Neural networks learn by adjusting the 'weights' of connections between neurons based on the error of their predictions, a process called backpropagation.