Machine learning

Machine learning gives computers the ability to learn without being explicitly programmed (Arthur Samuel, 1959).^[1]^[2] It is a subfield of computer science.

The idea came from work in artificial intelligence.^[3] Machine learning explores the study and construction of algorithms which can learn and make predictions on data.^[4] Such algorithms follow programmed instructions, but can also make predictions or decisions based on data.^[5]^: 2 They build a model from sample inputs.

References

↑ John McCarthy & Edward Feigenbaum 1990. In Memoriam Arthur Samuel: pioneer in machine learning. AI Magazine. AAAI. 11 (3).[1]
↑ Phil Simon (2013). Too big to ignore: the business case for big data. Wiley. p. 89. ISBN 978-1-118-63817-0.
↑ [2]
↑ Ron Kohavi; Foster Provost (1998). "Glossary of terms". Machine Learning. 30: 271–274.
↑ Christopher Bishop 1995. Neural networks for pattern recognition. Oxford University Press. ISBN 0-19-853864-2

[1] John McCarthy & Edward Feigenbaum 1990. In Memoriam Arthur Samuel: pioneer in machine learning. AI Magazine. AAAI. 11 (3).[1]

[arthur_samuel_machine_learning_def-2] Phil Simon (2013). Too big to ignore: the business case for big data. Wiley. p. 89. ISBN 978-1-118-63817-0.

[Britannica-3] [2]

[4] Ron Kohavi; Foster Provost (1998). "Glossary of terms". Machine Learning. 30: 271–274.

[bishop-5] Christopher Bishop 1995. Neural networks for pattern recognition. Oxford University Press. ISBN 0-19-853864-2

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