What is deep learning?
Q: What is deep learning?
A: Deep learning is a type of machine learning that uses neural networks to process information, and is often organized with at least one intermediate (hidden) layer between the input and output layers.
Q: What are the different kinds of learning sessions used in deep learning?
A: Deep learning can be organized into unsupervised, semi-supervised, and supervised learning sessions.
Q: What are some tasks that are easy for humans but difficult for computers to perform?
A: Tasks such as recognizing and understanding speech, images, or handwriting are easy for humans but difficult for computers to perform.
Q: What happens to information as it is processed in a multi-layer neural network?
A: In a multi-layer neural network, the information processed becomes more abstract with each added layer.
Q: What are deep learning models inspired by?
A: Deep learning models are inspired by information processing and communication patterns in biological nervous systems.
Q: How do deep learning models differ from the properties of biological brains?
A: Deep learning models are different from the structural and functional properties of biological brains, especially the human brain, in many ways, which makes them incompatible with neuroscience evidences.
Q: What is another term for deep learning?
A: Deep learning is also known as deep structured learning or hierarchical learning.
