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machine learning

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Főnév

machine learning (tsz. machine learnings)

  1. (informatika, mesterséges intelligencia, gépi tanulás) gépi tanulás

Sablon:short description Sablon:dynamic list Sablon:machine learning bar the following outline is provided as an overview of and topical guide to machine learning:

machine learning – a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence.[1] in 1959, arthur samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed".[2] machine learning involves the study and construction of algorithms that can learn from and make predictions on data.[3] these algorithms operate by building a model from an example training set of input observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.


Sablon:toc limit

what type of thing is machine learning?

paradigms of machine learning

applications of machine learning

machine learning hardware

machine learning tools

machine learning frameworks

proprietary machine learning frameworks

open source machine learning frameworks

machine learning libraries

machine learning algorithms

machine learning methods

instance-based algorithm

dimensionality reduction

dimensionality reduction

ensemble learning

ensemble learning

meta-learning

meta-learning

reinforcement learning

reinforcement learning

supervised learning

supervised learning

bayesian

bayesian statistics

decision tree algorithms

decision tree algorithm

linear classifier

linear classifier

unsupervised learning

unsupervised learning

artificial neural networks

artificial neural network

association rule learning

association rule learning

hierarchical clustering

hierarchical clustering

cluster analysis

cluster analysis

anomaly detection

anomaly detection

semi-supervised learning

semi-supervised learning

deep learning

deep learning

other machine learning methods and problems

machine learning research

history of machine learning

history of machine learning

machine learning projects

machine learning projects

machine learning organizations

machine learning organizations

machine learning conferences and workshops

machine learning publications

books on machine learning

machine learning journals

persons influential in machine learning

see also

other

  1. http://www.britannica.com/ebchecked/topic/1116194/machine-learning Sablon:tertiary source
  2. phil simon (march 18, 2013). too big to ignore: the business case for big data. wiley. p. 89. ISBN 978-1-118-63817-0. Check date values in: |date= (help)
  3. (1998) „glossary of terms”. machine learning 30, 271–274. o. DOI:10.1023/a:1007411609915.  
  4. Sablon:citation
  5. Lua-hiba a(z) package.lua modulban a(z) 80. sorban: module 'Module:Citation/CS1/Suggestions' not found