What is Deep Learning? – DATAVERSITY

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Deep Learning is a type of Machine Learning, using neural networks to grasp complex patterns. This type of technology allows Artificial Intelligence systems to perform human like tasks, “such as recognizing real-life objects or understanding speech.” While the operation of these brain-inspired networks remains inscrutable, their interconnected layers algorithms give machines the ability to be trained and carry out specific tasks. The algorithms that drive this process account for a greater number of and more abstract variables.

Other Definitions of Deep Learning Include:

  • “A specific type of Machine Learning where the learning happens in successive layers ˗ each layer adding knowledge of the previous layer.” (Paramita Ghosh, DATAVERSITY®)
  • “Technology that imitates the actions of a human brain, allowing software to train and explore an environment on its own, with minimal human intervention.” (Keith D Foote, DATAVERSITY®)
  • “A form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts.” (Goodfellow, et. al. Deep Learning, MIT Press)
  • “The cutting-edge of the cutting-edge technology focusing more narrowly on a subset of Machine Learning tools and techniques and applies them to solving” problems requiring thought. (Bernard Marr, Forbes)
  • “A branch of Artificial Intelligence inspired by the structure of the human brain…. [that gives] machines the ability to intuit the physical world.” (Aditya Singh, Harvard Business Review)
  • Software attempting “to mimic the activity in layers of neurons in the neocortex, the wrinkly 80 percent of the brain where thinking occurs. The software learns, in a very real sense, to recognize patterns in digital representations of sounds, images, and other data.” (Robert D Hof, MIT Technology Review)

Businesses use Deep Learning to:

 

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