Ubicación Física: 006.3 / M681
Machine learning / | |
Autor: | Mitchell, Tom M. |
Pié de imprenta: | Boston (Estados Unidos) : McGraw-Hill, 1997. |
Descripción: | 414 p. |
ISBN: | 9780070428072. |
Tema(s): | |
Resumen: | Machine Learning is the study of computer algorithms that improve automatically through experience. Successful applications range from data mining programs that discover general rules from large databases, to information filtering systems that learn users reading preferences, to autonomous vehicles that learn to drive on public highways. Machine Learning is an inherently interdisciplinary field, built on concepts from artificial intelligence, probability and statistics, information theory, philosophy, control theory, psychology, neurobiology, and other fields. This textbook provides a single source introduction to the primary approaches to machine learning. It is intended for advanced undergraduate and graduate students, as well as for developers and researchers in the field, No prior background in artificial intelligence or statistics is assumed. Several key algorithms, example date sets, and project-oriented homework assignments discussed in the book are accessible through the World Wide Web. |
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Navegando BIBLIOTECA SEDE LA CARO Estantes, Ubicación: Depósito, Código de colección: Colección General Cerrar el navegador de estanterías
006.3 / B622 Pattern recognition and machine learning / | 006.3 / B622 Pattern recognition and machine learning / | 006.3 / D918 Teamwork in multi-agent systems : a formal approach / | 006.3 / M681 Machine learning / | 006.3 / M681 Machine learning / | 006.31 / A456 Introduction to machine learning / | 006.31 / A456 Introduction to machine learning / |
Sistemas
Machine Learning is the study of computer algorithms that improve automatically through experience. Successful applications range from data mining programs that discover general rules from large databases, to information filtering systems that learn users reading preferences, to autonomous vehicles that learn to drive on public highways. Machine Learning is an inherently interdisciplinary field, built on concepts from artificial intelligence, probability and statistics, information theory, philosophy, control theory, psychology, neurobiology, and other fields. This textbook provides a single source introduction to the primary approaches to machine learning. It is intended for advanced undergraduate and graduate students, as well as for developers and researchers in the field, No prior background in artificial intelligence or statistics is assumed. Several key algorithms, example date sets, and project-oriented homework assignments discussed in the book are accessible through the World Wide Web.
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