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Title      : Data Analytics with R Programming
Subject      : Computer/Information Science
copyright © 2020   : Scitech Publications (India) Pvt Ltd
Author      : Bhuvaneswari V
Publisher      : Scitech Publications (India) Pvt Ltd
Chapters/Pages      : 11/224
Total Price      : Rs.      : 106
 
 
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Chapters
     
Contents Total views (0)  

Pages: 13
Price: Rs 0   
 
Chapter 1 * Data Analytics - An Insight Total views (0)  
Chapter 1 provides with brief insight of Data analytic, discussing evolution of data, data growth and data classification. The chapter presents with an introduction to data science and discusses data analytics classification categories and data preparation for data analytics. In addition a view of Big data, characteristics of big data, Hadoop and Map Reduce are presented. Finally the applications ......
Pages: 12
Price: Rs 6   
 
Chapter 2 * Understanding Data Total views (0)  
Chapter 2 introduces the data features for understanding and preparing data for analytics. The chapter discusses Data processing phases, Data Reduction techniques, Data Measurements, Data similarity and dissimilarity metrics for attribute analysis, Measures of variable types and Data distribution measures.
Pages: 9
Price: Rs 4.5   
 
Chapter 3 * Exploring R Basics Total views (0)  
Chapter 3 provides an introduction of getting started with R installation, environment, packages and library. This chapter also discusses R data types, operators in R and R objects with examples in R. The important data structures Lists, arrays, matrix, factors and data frame are also explained with R code for accessing group of data into R. This chapter finally discuss the file formats for export ......
Pages: 28
Price: Rs 14   
 
Chapter 4 * Data Visualization in R Total views (0)  
Chapter 4 provides an introduction to Exploratory Data Analytics and discusses visualization of data using R packages Lattice and ggplot. The packages are well explored for all plot types in lattice and ggplot with examples inferences. The code snippet for qplot are is given.
Pages: 34
Price: Rs 17   
 
Chapter 5 * Statistical Measures Total views (0)  
Chapter 5 presents methods of statistical measures for data analytics. The chapter discusses the measures of central tendency mean, median, mode, measure of variability, deviation analysis with examples explaining the spread of data distribution. The chapter also presents the data standardizing using z -Score, probability distributions, Parametric and Non parametric tests measures for hypothesis v ......
Pages: 25
Price: Rs 12.5   
 
Chapter 6 * Regression Analysis Total views (0)  
Chapter 6 provides with an introduction to regression models for predictive analytics. The chapter presents a methodological way of regression analysis steps, discuss the diagnostics of regression residuals and coefficients. The chapter also presents inference of regression residuals and diagnostic plots for linear and logistic regression models.
Pages: 11
Price: Rs 5.5   
 
Chapter 7 * Clustering and PCA Total views (0)  
Chapter 7 discusses clustering approach for data analytics. The various clustering methods are also discussed. The R packages for clustering k-means PAM, hclust are presented with use cases through a step by step approach. In addition the chapters also present the inference of diagnostic coefficients and measure of goodness of clusters. The chapter also discusses Principal component analysis for d ......
Pages: 19
Price: Rs 9.5   
 
Chapter 8 * Classification Total views (0)  
Chapter 8 introduces basic concepts of classification and classification approaches for developing prediction models. The chapter discusses feature selection attribute measures information gain, gini index and gain ratio. In addition the chapter presents detailed discussion of decision tree induction, random forest construction and bagging approaches for data prediction.. Use case are explained in ......
Pages: 27
Price: Rs 13.5   
 
Chapter 9 * Usecase-1: Regression Analysis/Usecase-2: Outlier Detection/Usecase-3: Sentiment Analysis Total views (0)  
Chapter 9 widely focuses on use cases for data analytics for various methods discussed in previous chapters. Three use cases are discussed with methodological steps and inferences. Use case in Regression analysis includes approaches for linear regression, logistic regression and multi linear regression. A use case for outlier analysis is discussed exploring different methods. A use case on sentime ......
Pages: 41
Price: Rs 20.5   
 
Glossary Total views (0)  

Pages: 5
Price: Rs 0