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

Deep learning is the subset of machine learning methods based on artificial neural networks (ANNs) with representation learning. The adjective "deep" refers to the use of multiple layers in the network. Methods used can be either 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:

• Bleeding edge technology
• a branch of machine learning
  • Artificial neural networks

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

• Graphics processing unit
• Tensor processing unit
• Vision processing unit

Deep learning software

Deep learning libraries

• DistBelief
• TensorFlow

Deep learning projects

• Google Brain

Deep learning organizations

Deep learning publications

Persons influential in deep learning

• Geoffrey Hinton
• Andrew Ng

See also

Further reading

• Understanding Convolutional Neural Networks (CNN), by Adit Deshpande, 2016
  • Part 1: A Beginner's Guide To Understanding Convolutional Neural Networks
  • Part 2: A Beginner's Guide To Understanding Convolutional Neural Networks, Part 2
  • Part 3: The 9 Deep Learning Papers You Need To Know About

References

External links

• Deep Learning Libraries by Language
• Data Science: Data to Insights from MIT (deep learning)