Data analytics with R (Record no. 4993)

MARC details
000 -LEADER
fixed length control field 06192nam a22002177a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230321181117.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230321b ||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788126576463
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.133
Item number MOT
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Motwani, Bharti
245 ## - TITLE STATEMENT
Title Data analytics with R
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc. Wiley India Pvt. Ltd.
Place of publication, distribution, etc. New Delhi
Date of publication, distribution, etc. 2022
300 ## - PHYSICAL DESCRIPTION
Extent xvii, 646 p.
365 ## - TRADE PRICE
Price type code INR
Price amount 729.00
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Table of content<br/>PART 1 Basics of R<br/><br/>Chapter 1 Introduction to R<br/><br/>1.1 Features of R<br/><br/>1.2 Installation of R<br/><br/>1.3 Getting Started<br/><br/>1.4 Variables in R<br/><br/>1.5 Input of Data<br/><br/>1.6 Output in R<br/><br/>1.7 In-Built Functions in R<br/><br/>1.8 Packages in R<br/><br/> <br/><br/>Chapter 2 Data Types of R<br/><br/>2.1 Vectors<br/><br/>2.2 Matrices<br/><br/>2.3 Arrays<br/><br/>2.4 Lists<br/><br/>2.5 Factors<br/><br/>2.6 Data Frame<br/><br/> <br/><br/>Chapter 3 Programming in R<br/><br/>3.1 Decision-Making Structures<br/><br/>3.2 Loops<br/><br/>3.3 User-Defined Functions<br/><br/>3.4 User-Defined Package<br/><br/>3.5 Reports using Rmarkdown<br/><br/> <br/><br/>Chapter 4 Data Exploration and Manipulation<br/><br/>4.1 Missing Data Management<br/><br/>4.2 Data Reshaping through Melting and Casting<br/><br/>4.3 Special Functions across Data Elements<br/><br/> <br/><br/>Chapter 5 Import and Export of Data<br/><br/>5.1 Import and Export of Data in Text File<br/><br/>5.2 Import and Export of Data in Excel<br/><br/>5.3 Import and Export of Data in XML<br/><br/>5.4 Import and Export of Data in JSON<br/><br/>5.5 Import and Export of Data in MySQL<br/><br/>5.6 Import and Export of Data in SPSS<br/><br/>5.7 Import and Export of Data in SAS<br/><br/>PART 2 Visualization Techniques<br/><br/>Chapter 6 Basic Visualization<br/><br/>6.1 Pie Chart<br/><br/>6.2 Bar Chart<br/><br/>6.3 Histograms<br/><br/>6.4 Line Chart<br/><br/>6.5 Kernel Density Plots<br/><br/>6.6 Quantile-Quantile (Q-Q) Plot<br/><br/>6.7 Box-and-Whisker Plot<br/><br/>6.8 Violin Plot<br/><br/>6.9 Dot Chart<br/><br/>6.10 Bubble Plot<br/><br/>6.11 Image Plot<br/><br/>6.12 Mosaic Plot<br/><br/> <br/><br/>Chapter 7 Advanced Visualization<br/><br/>7.1 Scatter Plot<br/><br/>7.2 Corrgrams<br/><br/>7.3 Star and Segment Plots<br/><br/>7.4 Tree Maps<br/><br/>7.5 Heat Map<br/><br/>7.6 Perspective and Contour Plot<br/><br/>7.7 Using ggplot2 for Advanced Graphics<br/><br/>PART 3 Statistical Analysis<br/><br/>Chapter 8 Basic Statistics<br/><br/>8.1 Descriptive Statistics<br/><br/>8.2 Table in R<br/><br/>8.3 Correlation and Covariance<br/><br/>8.4 Simulation and Distributions<br/><br/>8.5 Reproducing Same Data<br/><br/>Case Study: Web Analytics using Goal Funnels: Asset for e-Commerce Business<br/><br/> <br/><br/>Chapter 9 Compare Means<br/><br/>9.1 Parametric Techniques<br/><br/>Case Study: Green Building Certification<br/><br/>Case Study: Comparison of Personal Web Store and Marketplaces for Online Selling<br/><br/>Case Study: Effect of Training Program on Employee Performance<br/><br/>Case Study: Effect of Demographics on Online Mobile Shopping Apps<br/><br/>9.2 Non-Parametric Tests<br/><br/> <br/><br/>Chapter 10 Time-Series Models<br/><br/>10.1 Time-Series Object in R<br/><br/>10.2 Smoothing<br/><br/>10.3 Seasonal Decomposition<br/><br/>10.4 ARIMA Modeling<br/><br/>10.5 Survival Analysis<br/><br/>Case Study: Foreign Trade in India<br/><br/> <br/><br/>PART 4 Machine Learning<br/><br/>Chapter 11 Unsupervised Machine Learning Algorithms<br/><br/>11.1 Dimensionality Reduction<br/><br/>Case Study: Balanced Scorecard Model for Measuring Organizational Performance<br/><br/>Case Study: Employee Attrition in an Organization<br/><br/>11.2 Clustering<br/><br/>Case Study: Market Capitalization Categories<br/><br/>Case Study: Performance Appraisal in Organizations<br/><br/> <br/><br/>Chapter 12 Supervised Machine Learning Problems<br/><br/>12.1 Regression<br/><br/>Case Study: Relationship between Buying Intention and Awareness of Electric Vehicles<br/><br/>Case Study: Application of Technology Acceptance Model in Cloud Computing<br/><br/>Case Study: Impact of Social Networking Websites on Quality of Recruitment<br/><br/>12.2 Classification<br/><br/>Case Study: Prediction of Customer Buying Intention due to Digital Marketing<br/><br/> <br/><br/>Chapter 13 Supervised Machine Learning Algorithms<br/><br/>13.1 Naïve Bayes Algorithm<br/><br/>Case Study: Measuring Acceptability of a New Product<br/><br/>13.2 k-Nearest Neighbor’s (KNN) Algorithm<br/><br/>Case Study: Predicting Phishing Websites<br/><br/>Case Study: Loan Categorization<br/><br/>13.3 Support Vector Machines (SVMs)<br/><br/>Case Study: Fraud Analysis for Credit Card and Mobile Payment Transactions<br/><br/>Case Study: Diagnosis and Treatment of Diseases<br/><br/>13.4 Decision Trees<br/><br/>Case Study: Occupancy Detection in Buildings<br/><br/>Case Study: Artificial Intelligence and Employment<br/><br/> <br/><br/>Chapter 14 Supervised Machine Learning Ensemble Techniques<br/><br/>14.1 Bagging<br/><br/>Case Study: Measuring Customer Satisfaction related to Online Food Portals<br/><br/>Case Study: Predicting Income of a Person<br/><br/>14.2 Random Forest<br/><br/>Case Study: Writing Recommendation/Approval Reports<br/><br/>Case Study: Prediction of Sports Results<br/><br/>14.3 Gradient Boosting<br/><br/>Case Study: Impact of Online Reviews on Buying Behavior<br/><br/>Case Study: Effective Vacation Plan through Online Services<br/><br/> <br/><br/>Chapter 15 Machine Learning for Text Data<br/><br/>15.1 Text Mining<br/><br/>Case Study: Spam Protection and Filtering<br/><br/>15.2 Sentiment Analysis<br/><br/>Case Study: Determining Online News Popularity<br/><br/> <br/><br/>Chapter 16 Neural Network Models (Deep Learning)<br/><br/>16.1 Steps for Building a Neural Network Model<br/><br/>16.2 Multilayer Perceptrons Model (2D Tensor)<br/><br/>Case Study: Measuring Quality of Products for Acceptance or Rejection<br/><br/>16.3 Recurrent Neural Network Model (3D Tensor)<br/><br/>Case Study: Financial Market Analysis<br/><br/>16.4 Convolutional Neural Network Model (4D Tensor)<br/><br/>Case Study: Facial Recognition in Security Systems<br/><br/>Answers to Objective Type Questions<br/><br/>Index<br/><br/>
520 ## - SUMMARY, ETC.
Summary, etc. Data analysis is the method of examining, cleansing, and modeling with the objective of determining useful information for effective decision-making and operations. It includes diverse techniques and tools and plays a major role in different business, science and social science areas. R software provides numerous functions and packages for using different techniques for producing desired outcome. Data Analytics with R will enable readers gain sufficient knowledge and experience to perform analysis using different analytical tools available in R. Each chapter begins with a number of important and interesting examples taken from a variety of sectors.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information visualization
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element R (Computer program language)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Bill No Bill Date Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total Checkouts Full call number Accession Number Date last seen Copy number Cost, replacement price Price effective from Koha item type
    Dewey Decimal Classification     IT & Decisions Sciences TB3162 16-02-2023 Indian Institute of Management LRC Indian Institute of Management LRC General Stacks 03/21/2023 Technical Bureau India Pvt. Ltd. 510.30   005.133 MOT 004853 03/21/2023 1 729.00 03/21/2023 Book

©2019-2020 Learning Resource Centre, Indian Institute of Management Bodhgaya

Powered by Koha