R Course

Description

How R Works

  • Data mining Using Statistical packages
  • A Few concepts Before Starting

R-Packages /Sorting

  • R-Calculator
  • Assigning Values To Variables
  • Vector Creation                                   
  • Generating Repeats
  • What is rep Function
  • Generating Factor Levels
  • Sorting Process 
  • Transpose Function                                  
  • Stack Function Used

Functions & Reading Data from External Files

  • Merge Function
  • Strsplit Function
  • Matrices
  • Matrix Manipulation
  • Row Sums

Generating Plots and Pie Charts

  • Line Plots
  • Bar Plots
  • Bar Plots For Population
  • Histogram
  • Pie Chart Components

Analysis of Variancy (ANOVA)

  • One Way Analysis of Variance
  • Two Way Analysis of Variance

What is Cluster Analysis

  • K-Means Clustering
  • Cluster Algorithm Working

Association Rule Mining Affinity Analysis

  • Association Rule Mining Affinity Analysis

Two Variable RelationShips

  • Linear Regression
  • Dependent And Independent Variables
  • Scatter Plots

Database connectivity & Logistic Regression

  • Logistic Regression
  • Examples of Logistic Regression
  • Logistic Regression in R
  • Predication

ROC Curve in R

  • Confusion Matrix
  • ROC Curve in R
  • Sensitivity & Specificity
  • Data Base Connectivity RODBC
  • Reading Data to ODBC Tables
  • Function (Mean)
  • Examples Of Function

Integrating R with Hadoop

  • Methods to integrate two popular open source softwares for Big Data analytics: R and Hadoop
  • -Integrating R with Hadoop using RHadoop and RMR package
  • Exploring RHIPE (R Hadoop Integrated Programming Environment)
  • Writing MapReduce Jobs in R and executing them on Hadoop

Case Study-Project Work

  • Predict Annual Restaurant Sales Based on Objective Measurement
  • Data Overview
  • Data Fields
  • Evaluation using RMSE
  • Feature Engineering / Selection

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