Deep learning falls under the umbrella of machine learning which is a subset of artificial intelligence (AI). Loosely defined, artificial intelligence encompasses technology that simulates human capabilities while machine learning algorithms learn and adapt to new events. Deep learning is a term for technologies that use artificial neural network (ANNs) algorithms. Experts consider deep learning and ANNs to be the same thing and use the terms interchangeably. Just like neural networks in brains, ANNs have neurons (nodes) interconnected by synapses (links). Each node receives data, performs an operation, and passes the new data to another node via a link. The links contain weights or biases that influence the next node’s operation.

- Henry H. Eckerson in Deep Learning Technology Isn’t New, So Why Is It A Big Deal Now?

April 3, 2017 (Blog)

Deep learning on the other hand is a sub-group of machine learning-algorithms (mostly variations of neural networks [1]) that try to move machine learning closer to the idea of artificial intelligence. Deep learning is at the moment mainly used to process highly unstructured content like images, videos or audio. For example if you talk to your smartphone, you are actually talking to an automatic speech recognition algorithm based on deep learning techniques.

- Julian Ereth in How Deep is your Data?

June 5, 2016 (Blog)