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Karl Jones: Created page with "'''Deep learning''' (also known as '''deep structured learning''', '''hierarchical learning''' or '''deep machine learning''') is a branch of machine learning based on a s..."

2016-09-01T12:16:55Z

Created page with "'''Deep learning''' (also known as '''deep structured learning''', '''hierarchical learning''' or '''deep machine learning''') is a branch of machine learning based on a s..."

New page

'''Deep learning''' (also known as '''deep structured learning''', '''hierarchical learning''' or '''deep machine learning''') is a branch of [[machine learning]] based on a set of [[Algorithm|algorithms]] that attempt to model high-level abstractions in [[data]] by using a deep graph with multiple processing layers, composed of multiple linear and non-linear transformations (see [[Linear map]]).

== Description ==

Deep learning is part of a broader family of [[machine learning]] methods based on learning representations of data.

An observation (e.g., an image) can be represented in many ways such as a vector of intensity values per pixel, or in a more abstract way as a set of edges, regions of particular shape, etc. Some representations are better than others at simplifying the learning task (e.g., face recognition or facial expression recognition).

One of the promises of deep learning is replacing handcrafted features with efficient algorithms for unsupervised or semi-supervised feature learning and hierarchical feature extraction.

Research in this area attempts to make better representations and create models to learn these representations from large-scale unlabeled data. Some of the representations are inspired by advances in neuroscience and are loosely based on interpretation of information processing and communication patterns in a nervous system, such as neural coding which attempts to define a relationship between various stimuli and associated neuronal responses in the brain.

Various deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks have been applied to fields like [[computer vision]], automatic [[speech recognition]], [[natural language processing]], [[audio recognition]], and [[bioinformatics]].

Deep learning has been characterized as a buzzword, or a rebranding of [[Neural network|neural networks]].

== See also ==

* [[Applications of artificial intelligence]]
* [[Boltzmann machine]]
* [[Compressed Sensing]]
* [[Connectionism]]
* [[Data mining]]
* [[Echo state network]]
* [[List of artificial intelligence projects]]
* [[Liquid state machine]]
* [[List of datasets for machine learning research]]
* [[Machine learning]]
* [[Neural network]]
* [[Reservoir computing]]
* [[Sparse coding]]

== External links ==

* [https://en.wikipedia.org/wiki/Deep_learning Deep learning] @ Wikipedia.org

[[Category:Artificial intelligence]]

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 * [[Applications of artificial intelligence]]
 * [[Boltzmann machine]]
-* [[Caffe (software)]] - a deep
+* [[Caffe (software)]] - a deep learning platform
 * [[Compressed Sensing]]
 * [[Connectionism]]

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 * [[Machine learning]]
 * [[Neural network]]
 * [[Reservoir computing]]
 * [[Sparse coding]]

Deep learning - Revision history

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Karl Jones: Created page with "'''Deep learning''' (also known as '''deep structured learning''', '''hierarchical learning''' or '''deep machine learning''') is a branch of machine learning based on a s..."