Efficient Learning Machines Theories, Concepts, and Applications for Engineers and System Designers

dc.contributor.authorMariette Awad.
dc.contributor.authorRahul Khanna.
dc.date.accessioned2025-10-13T16:45:07Z
dc.date.available2025-10-13T16:45:07Z
dc.date.issued2015
dc.descriptionLibro electrónico.
dc.description.abstractMachine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques.
dc.identifier.isbn978-1-4302-5990-9
dc.identifier.otherhttps://doi.org/10.1007/978-1-4302-5990-9
dc.identifier.urihttps://link.springer.com/openurl?genre=book&isbn=978-1-4302-5990-9
dc.identifier.urihttp://bibliovirtual.umar.mx:4000/handle/123456789/492
dc.language.isoen_US
dc.publisherApress
dc.titleEfficient Learning Machines Theories, Concepts, and Applications for Engineers and System Designers
dc.typeBook
eperson.firstnamenombre
person.jobTitletrabajo

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