Deep learning heavily utilizes these networks, especially for complex pattern recognition.
Image recognition tasks have greatly benefited from the precision of neural networks.
Training methods, such as backpropagation, play a crucial role in adjusting the weights between nodes.
Regularization techniques, like dropout, are essential in preventing overfitting in extensive networks.
Artificial Neural Networks are inspired by the human brain, with interconnected nodes similar to neurons.