03409nam a22005175i 4500 ssj0001762294 WaSeSS 20251230090103.0 m d cr n 161227s2017 xxu| o |||| 0|eng d 9781484225141 9781484225134 (print) 9781484256770 WaSeSS AIMIT LIBRARY QA76.9.B45 UN bicssc COM021000 bisacsh UN thema 005.764 HODU Hodeghatta, Umesh R. 31322 Business analytics using R : By Umesh R. Hodeghatta and Umesha Nayak. practical approach / 1st ed. 2017. London : Apress , 2022. xvii,280 p.; PB 24.5 cm. text file PDF rda Requires an SPL library card. Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. You will: • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem. Mode of access: World Wide Web. Business analytics process and data exploration 31323 Supervised machine learning 31324 Simple linear regression 31325 Big data analysis 31326 Electronic books. local 31327 Nayak, Umesha. 31328 SpringerLink (Online service) 31329 O'Reilly (Firm) 31330 Serials Solutions 31331 Springer eBooks Printed edition: 9781484225134 Printed edition: 9781484225158 View this electronic item in O'Reilly Online Learning: Academic/Public Library Edition. https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484225141/?ar An e-book available through full-text database. ddc BK 1st ed. 005.764 HODU 222584 222584 03645878 0 0 ddc 0 0 MCA AIMIT AIMIT 2022-03-24 Biblios Book Point 749.00 Bill no:6627; Bill dt:2022-03-23 0 005.764 HODU MCA17132 2025-07-21 00:00:00 599.00 2022-04-23 BK 0 0 ddc 0 0 MCA AIMIT AIMIT 2022-03-24 Biblios Book Point 749.00 Bill no:6627; Bill dt:2022-03-23 0 005.764 HODU MCA17133 2025-07-21 00:00:00 599.00 2022-04-23 BK