Deep learning
Derin öğrenme
D2
Deep learning is an approach to machine learning that uses models with layered representations of a target function.
Review status: 2027-08-28
Technical explanation
Deep feedforward networks learn a parameterized mapping from inputs to outputs through intermediate computations that form layers.
Conceptual boundaries
Deep learning is not synonymous with every neural network, because neural networks can have different structures and depth is a property of their layered composition.
Provider-neutral example
A team can use a deep feedforward model to turn image features into a suggested category while a person confirms the result.
Limitations
Approximating a target function is a modeling goal, not proof of accuracy in a specific deployment.
Related concepts
Atomic claims and evidence
1.1Goodfellow, Bengio, and Courville, Deep Learning, Introduction
- Source
- Goodfellow, Bengio, and Courville, Deep Learning, Introduction
- Source role
- Authoritative source
- Exact locator
- Introduction, p. 8: deep learning as an approach to AI and a type of machine learning
- Supported claim
- Deep learning is an approach to artificial intelligence and a type of machine learning, and deep feedforward networks are described as quintessential deep-learning models.
- Last verification
- Review due
- Scope limitation
- This identifies a major model class and does not make every AI system a deep-learning system.
1.2Goodfellow, Bengio, and Courville, Deep Learning, Chapter 6
- Source
- Goodfellow, Bengio, and Courville, Deep Learning, Chapter 6
- Source role
- Authoritative source
- Exact locator
- Chapter 6, p. 164: Deep Feedforward Networks as quintessential deep-learning models
- Supported claim
- Deep learning is an approach to artificial intelligence and a type of machine learning, and deep feedforward networks are described as quintessential deep-learning models.
- Last verification
- Review due
- Scope limitation
- This identifies a major model class and does not make every AI system a deep-learning system.
2.1Goodfellow, Bengio, and Courville, Deep Learning, Chapter 6
- Source
- Goodfellow, Bengio, and Courville, Deep Learning, Chapter 6
- Source role
- Authoritative source
- Exact locator
- Chapter 6, p. 164: goal of a feedforward network and learned parameters
- Supported claim
- A deep feedforward network defines an input-to-output mapping and learns parameters that improve its approximation of a target function.
- Last verification
- Review due
- Scope limitation
- Approximation of a target function is a modeling goal, not proof of accuracy in every deployment context.