deep learning

American  

[deep lur-ning] / ˈdip ˌlɜr nɪŋ /

noun

Computers.

1. an advanced type of machine learning that uses multilayered neural networks to establish nested hierarchical models for data processing and analysis, as in image recognition or natural language processing, with the goal of self-directed information processing.

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Etymology

Origin of deep learning

First recorded in 1985–90

Example Sentences

By applying deep learning models trained on tens of thousands of MRI scans, the team estimated the "brain age" of different regions in each hemisphere and examined how stroke affects both structure and recovery.

From Science Daily

"Based on the principle of polarization holography, we used a deep learning architecture known as a convolutional neural network model to enable the use of polarization as an independent information dimension."

From Science Daily

He redoubled his wooing of individual researchers and invited Yann LeCun, the deep learning pioneer based at New York University, over for another recruitment dinner.

From The Wall Street Journal

The researchers also note that inverse-design methods, including genetic algorithms and deep learning, could help speed up device optimization and support real-world system deployment.

From Science Daily

“People should stop training radiologists now. It’s just completely obvious that within five years, deep learning is going to do better than radiologists.”

From The Wall Street Journal