Outline of machine learning

<p>The following <a href="/facts/Outline_(list)/uUpf6Jh6">outline</a> is provided as an overview of, and topical guide to, machine learning:
</p><p>Machine learning (ML) is a subfield of <a href="/facts/Artificial_intelligence/lJGauQwX">artificial intelligence</a> within <a href="/facts/Computer_science/lN3pEyPz">computer science</a> that evolved from the study of <a href="/facts/Pattern_recognition/o1s38opj">pattern recognition</a> and <a href="/facts/Computational_learning_theory/DKMoukIr">computational learning theory</a>. In 1959, <a href="/facts/Arthur_Samuel_(computer_scientist)/hjG9AfX2">Arthur Samuel</a> defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". ML involves the study and construction of <a href="/facts/Algorithm/fnl5NmRt">algorithms</a> that can <a href="/facts/Learning/lehEKRjC">learn</a> from and make predictions on <a href="/facts/Data/AUBFN97o">data</a>. These algorithms operate by building a <a href="/facts/Mathematical_model/CGhyuxgz">model</a> from a <a href="/facts/Training%2c_validation%2c_and_test_data_sets/V3mMQb2G">training set</a> of example observations to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
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Outline of machine learning open-in-new

Outline of machine learning