Deep learning is a subset of machine learning methods based on neural networks with representation learning. Methods used can be supervised, semi-supervised, or unsupervised. Deep learning architectures have been applied to various fields and are able to extract better features than shallow models through a hierarchy of layers to transform input data into a slightly more abstract representation. The word "deep" refers to the number of layers through which the data is transformed, with deep models being able to learn features effectively. Advances in hardware have driven renewed interest in deep learning, with GPUs playing a crucial role in speeding up training algorithms.
