株式会社極東書店トップ商品一覧Practical Data Mining Techniques and Applications.

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Practical Data Mining Techniques and Applications.

Practical Data Mining Techniques and Applications.

・ISBN 978-1-032-23267-6 hard GB£ 171.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003390220
著者・編者Shah, Ketan / Shah, Neepa / Sawant, Vinaya / Parolia, Neeraj (eds.),
出版社 (Auerbach, UK)
出版年月2023
ページ数200 pp.
言語ENG
ニュース番号<A01-65466>

解説

Data mining techniques and algorithms are extensively used to build real-world applications. A practical approach can be applied to data mining techniques to build applications. Once deployed, an application enables the developers to work on the users' goals and mold the algorithms with respect to users' perspectives.

Practical Data Mining Techniques and Applications focuses on various concepts related to data mining and how these techniques can be used to develop and deploy applications. The book provides a systematic composition of fundamental concepts of data mining blended with practical applications. The aim of this book is to provide access to practical data mining applications and techniques to help readers gain an understanding of data mining in practice. Readers also learn how relevant techniques and algorithms are applied to solve problems and to provide solutions to real-world applications in different domains. This book can help academicians to extend their knowledge of the field as well as their understanding of applications based on different techniques to gain greater insight. It can also help researchers with real-world applications by diving deeper into the domain. Computing science students, application developers, and business professionals may also benefit from this examination of applied data science techniques.

By highlighting an overall picture of the field, introducing various mining techniques, and focusing on different applications and research directions using these methods, this book can motivate discussions among academics, researchers, professionals, and students to exchange and develop their views regarding the dynamic field that is data mining.