Data analytics using R
Language: ENG Publication details: Chennai McGraw Hill Education 2018Description: xxiii, 555p. | Binding - Paperback | 24.2*18.5 cmISBN:- 9789352605248
- DDC23 006.312 ACH
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School of Engineering & Technology Reference Section | Reference | 006.312 ACH (Browse shelf(Opens below)) | Not For Loan | E14936 | ||
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School of Engineering & Technology General Stacks | Circulation | 006.312 ACH (Browse shelf(Opens below)) | Checked out to Zakaullah Ansari (ITF04) | 07/10/2025 | E14938 | |
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School of Engineering & Technology General Stacks | Circulation | 006.312 ACH (Browse shelf(Opens below)) | Available | E14939 | ||
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School of Engineering & Technology General Stacks | Circulation | 006.312 ACH (Browse shelf(Opens below)) | Available | E14940 |
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| 006.31 OSI Deep learning cookbook | 006.312 ACH Data analytics using R | 006.312 ACH Data analytics using R | 006.312 ACH Data analytics using R | 006.312 ACH Data analytics using R | 006.312 BPB Data Mining | 006.312 BPB Data Mining |
This book is aimed at undergraduate students of computerscience and engineering. The book will be useful companion for IT professionalsto data analysts and decision makers responsible for driving strategicinitiatives, and management graduates and business analysts, engaged inself-study.
This book by Acharya unleashes the power of R as astatistical data analytics and visualization tool and introduces the learnersto several data mining algorithms and chart forms / visualizations. It has goodemphasis on ‘asking the right questions’.
CONTENT:
Chapter 1 Introduction to R
Chapter 2 Getting Started with R
Chapter 3 Loading and Handling Data in R
Chapter 4 Exploring Data in R
Chapter 5 Linear Regression using R
Chapter 6 Logistic Regression
Chapter 7 Decision Tree
Chapter 8 Time Series in R
Chapter 9 Clustering
Chapter 10 Association Rules
Chapter 11 Text Mining
Chapter 12 Parallel Computing with R
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