A neural network is a type of machine learning algorithm modeled after the human brain. It is composed of layers of interconnected nodes, which process inputs and generate outputs. Neural networks are typically used for supervised learning tasks, such as classification and regression.
A deep learning network is a type of neural network that is composed of multiple layers of neurons. This allows the network to learn more complex patterns and relationships between data. Deep learning networks are typically used for unsupervised learning tasks, such as clustering and object recognition.
For example, a neural network can be used to classify images of cats and dogs. It will take the input image and output a label of either cat or dog. A deep learning network, on the other hand, can be used to recognize objects in the image, such as a person, a car, or a tree. It will take the input image and output a list of objects it has identified.