Deep LearningDeep learning is part of a broader family of machine learning methods basedon artificial neural netorks with representation learning. Learning canbe supervised, semi-supervised or unsupervised.Deep-learning architectures such as deep neural networks, deep beliefnetworks, deep reinforcement learning, recurrent neural networks and convolutionalneural networks have been alied to fields including computer vision, speechrecognition, natural language processing, machine translation, bioinformatics, drugdesign, medical image analysis, material inspection and board gme programs, wherethey have producd results cmparable to and in some cases surpassing humanexpert performance.Artificial neurl networks (ANNs were inspired by information processng anddistributed communication nodes in biologial systems. ANNs have variousdifferences frm biological brains. Specifically, artificial neral networks tend to be staticand symbolic, while the biological bain omost living organisms is dynamic (plastic)and analogue.The adjective "deep" in deepearning refers to the use of multiple layers in the networ.
