Hiển thị biểu ghi dạng vắn tắt

dc.contributor.authorShmueli, Galit
dc.contributor.authorGedeck, Peter
dc.contributor.authorC. Bruce, Peter
dc.contributor.authorYahav, Inbal
dc.contributor.authorR. Patel, Nitin
dc.date.accessioned2024-07-16T07:21:00Z
dc.date.available2024-07-16T07:21:00Z
dc.date.issued2023
dc.identifier.isbn978-1-119-83517-2
dc.identifier.urihttps://thuvienso.hoasen.edu.vn/handle/123456789/15479
dc.description688 pagesvi
dc.description.abstractMachine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.vi
dc.language.isoenvi
dc.publisherWileyvi
dc.subjectMachine Learningvi
dc.subjectBusiness Analyticsvi
dc.titleMachine Learning for Business Analytics: Concepts, Techniques, and Applications in R (2nd Edition)vi
dc.typeBookvi


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Hiển thị biểu ghi dạng vắn tắt