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What is Deep Learning?

Deep learning is a subset of machine learning that utilizes artificial neural networks (ANNs) to learn how to recognize patterns in data. ANNs are composed of interconnected processing nodes, called neurons, that can learn to recognize patterns of input data. Deep learning algorithms can be used to recognize patterns in data of varying complexity, including data that is handwritten, spoken, or visual.

Deep learning algorithms have been responsible for some of the most impressive recent advances in machine learning, including the ability to accurately recognize objects in images and to understand natural language. Deep learning algorithms are also being used to develop autonomous vehicles, to create intelligent assistants, and to improve the accuracy of financial predictions.

The deep learning algorithms used in these applications are modeled after the brain. The brain is composed of a vast number of interconnected neurons that can learn to recognize patterns of input data. Deep learning algorithms are able to learn more effectively than traditional machine learning algorithms by using more layers of neurons in their networks.

The use of deep learning algorithms is growing rapidly. A recent study by Tractica found that the global market for deep learning technology will grow from $643.8 million in 2016 to $11.1 billion by 2021.


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