Difference between revisions of "Deep learning"

Latest revision as of 15:14, 3 September 2016

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 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 networks.

See also

• Applications of artificial intelligence
• Boltzmann machine
• Caffe (software) - a deep learning platform
• 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
• PaddlePaddle - a deep learning platform
• Reservoir computing
• Sparse coding

External links

• Deep learning @ Wikipedia.org