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dc.contributor.editorZhang, Yagang
dc.date.accessioned2021-04-20T14:56:16Z
dc.date.available2021-04-20T14:56:16Z
dc.date.issued2010
dc.identifierONIX_20210420_9789533070339_174
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/64818
dc.description.abstractMachine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large amount of knowledge about machine learning and practice presented in the book, it is divided into three major parts: Introduction, Machine Learning Theory and Applications. Part I focuses on the introduction to machine learning. The author also attempts to promote a new design of thinking machines and development philosophy. Considering the growing complexity and serious difficulties of information processing in machine learning, in Part II of the book, the theoretical foundations of machine learning are considered, and they mainly include self-organizing maps (SOMs), clustering, artificial neural networks, nonlinear control, fuzzy system and knowledge-based system (KBS). Part III contains selected applications of various machine learning approaches, from flight delays, network intrusion, immune system, ship design to CT and RNA target prediction. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners.
dc.languageEnglish
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UG Graphical & digital media applicationsen_US
dc.titleMachine Learning
dc.typebook
oapen.identifier.doi10.5772/217
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9789533070339
oapen.relation.isbn9789535158998
oapen.imprintIntechOpen
oapen.pages446


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