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Machine learning
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<p>Machine learning (ML) is a <a href="/facts/Field_of_study/pKoQHpYL">field of study</a> in <a href="/facts/Artificial_intelligence/lJGauQwX">artificial intelligence</a> concerned with the development and study of <a href="/facts/Computational_statistics/noW2SBX8">statistical algorithms</a> that can learn from <a href="/facts/Data/AUBFN97o">data</a> and <a href="/facts/Generalize/v0b1pwUx">generalize</a> to unseen data, and thus perform <a href="/facts/Task_(computing)/ghdT0IkM">tasks</a> without explicit <a href="/facts/Machine_code/bgdQ1Fxf">instructions</a>. Within a subdiscipline in machine learning, advances in the field of <a href="/facts/Deep_learning/JLuwD3ea">deep learning</a> have allowed <a href="/facts/Neural_network_(machine_learning)/6V1jMlkx">neural networks</a>, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. </p><p>ML finds application in many fields, including <a href="/facts/Natural_language_processing/1hjMKsSN">natural language processing</a>, <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a>, <a href="/facts/Speech_recognition/z7S7Pgk6">speech recognition</a>, <a href="/facts/Email_filtering/aKxq5uSf">email filtering</a>, <a href="/facts/Agriculture/TGztqzJs">agriculture</a>, and <a href="/facts/Medicine/2fnp90Je">medicine</a>. The application of ML to business problems is known as <a href="/facts/Predictive_analytics/tbqzk5qe">predictive analytics</a>. </p><p><a href="/facts/Statistics/DNPsKGYU">Statistics</a> and <a href="/facts/Mathematical_optimization/oRn8Iv5I">mathematical optimization</a> (mathematical programming) methods comprise the foundations of machine learning. <a href="/facts/Data_mining/AH53q5ac">Data mining</a> is a related field of study, focusing on <a href="/facts/Exploratory_data_analysis/8hvnf7JS">exploratory data analysis</a> (EDA) via <a href="/facts/Unsupervised_learning/8a6f61MC">unsupervised learning</a>. </p><p>From a theoretical viewpoint, <a href="/facts/Probably_approximately_correct_learning/vBQlvDV1">probably approximately correct learning</a> provides a framework for describing machine learning. </p>