deep learning
(description of machine learning using substantial neural networks)
Deep learning is a buzzword that has been used a number of ways
regarding high-capability machine learning (ML) systems. Among the ways:
- basically just to describe the workings of neural networks, a type of AI system inspired by the structure of nervous systems.
- specifically those that use feedback to improve their performance.
- specifically those that loop data back through, a means of implementing feedback.
- specifically those with numerous layers (i.e., above some given threshold number).
Neural networks are generally organized in a series of layers of
(artificial) neurons (programs that process data much like a
nervous system's neuron does): input data to a neuron in a layer
after the first is from multiple neurons in the first layer, and
its output is directed to multiple neurons in the following layer.
As computing progress has allowed larger (and deeper) such networks
to be implemented practically, the term deep learning has been
used to distinguish the computation of such deeper networks.
(computing,machine learning)
Further reading:
https://en.wikipedia.org/wiki/Deep_learning
https://www.mathworks.com/discovery/deep-learning.html
https://www.ibm.com/topics/deep-learning
https://aws.amazon.com/what-is/deep-learning/
https://levity.ai/blog/difference-machine-learning-deep-learning
https://www.dataversity.net/brief-history-deep-learning/
https://indico.cern.ch/event/683620/contributions/3420614/attachments/1840352/3017035/Lab_Infieri_LabPresentation.pdf
https://ui.adsabs.harvard.edu/abs/2023RSOS...1021454S/abstract
Referenced by pages:
machine learning (ML)
neural network (NN)
Index