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Deep Learning

DEEP LURN-ing /diːp ˈlɜːrnɪŋ/

nounC1GRETOEFLIELTS

formaltechnical

A subfield of Machine Learning that uses Neural Networks with multiple layers (deep architectures) to learn complex patterns from large amounts of data.

The 'deep' in Deep Learning refers to the number of hidden layers in the neural network architecture. These multiple layers allow the network to learn hierarchical representations of data, extracting increasingly abstract features, which is crucial for tasks like image and speech recognition.

The story behind the word. The term 'Deep Learning' gained prominence in the 2000s, building upon the foundations of 'Machine Learning' and 'Neural Networks.' The 'deep' refers to the multiple hidden layers within the neural network architectures used, distinguishing them from earlier, shallower networks. These multiple layers allow for the learning of increasingly abstract and complex representations of data, leading to powerful advancements in AI.

Commonly confused with

Machine Learning: Deep Learning is a specialized subfield of Machine Learning that uses multi-layered neural networks.
Neural Network: Deep Learning specifically refers to Neural Networks with many hidden layers, enabling them to learn more complex representations.

Word family

deep-learned (adjective): Acquired or developed through deep learning.

Collocations

Deep Learning algorithms
Deep Learning model
Deep Learning architecture
Deep Learning frameworks

Example sentences

"Recent advancements in Deep Learning have enabled AI systems to achieve near-human performance in tasks like image classification and natural language processing." Discussing breakthroughs in AI.
"Training a Deep Learning model requires significant computational resources and large datasets." A technical explanation.

Memory hook

Think of 'deep' as 'many layers' in a 'learning' system, like digging deep into data to find hidden insights. Multi-Layered Learning

When not to use

Do not use 'Deep Learning' as a general term for all Machine Learning or AI. It is a specific, powerful subset that uses multi-layered neural networks.

Fun facts

The success of Deep Learning is largely attributed to the availability of massive datasets and powerful GPUs (Graphics Processing Units) for computation.
AlphaGo, the AI that defeated the world champion Go player, was a prominent example of Deep Learning's capabilities.

Explore more words

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