Draft:Outline of deep learning Source: en.wikipedia.org/wiki/Draft:Outline_of_deep_learning

The following outline is provided as an overview of and topical guide to deep learning:

In machine learning, deep learning focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data. The adjective "deep" refers to the use of multiple layers (ranging from three to several hundred or thousands) in the network. Methods used can be supervised, semi-supervised or unsupervised.

Other names for deep learning

Deep machine learning
Deep structured learning
Hierarchical learning

What type of thing is deep learning?

Deep learning can be described as all of the following:

A type of technology
- Bleeding edge technology
- Computer technology
  - Artificial neural networks
A branch of science
- A branch of applied science
  - A branch of computer science
    - A branch of artificial intelligence
      - a branch of machine learning

Branches of deep learning

History of deep learning

History of deep learning

Deep learning architectures

Applications of deep learning technology

Pattern recognition –
- Speech recognition –
- Image recognition –
Classification –
- Topic classification –
- Topic classification –
- Sentiment analysis –
- Question answering –
- Language translation –
Drug discovery –
Toxicology –
Customer relationship management –
Recommendation systems –
Biomedical informatics –

Deep learning hardware

Deep learning software

Deep learning libraries

Deep learning projects

Google Brain

Deep learning organizations

Deep learning publications

Persons influential in deep learning

See also

Further reading

Understanding Convolutional Neural Networks (CNN), by Adit Deshpande, 2016

References

External links

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