R Data Analysis Solutions - Machine Learning Techniques [Video]
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Free ChapterAcquire and Prepare the Ingredients – Your Data
- The Course Overview
- Reading Data from CSV Files
- Reading XML and JSON Data
- Reading Data from Fixed-Width Formatted Files, R Files, and R Libraries
- Removing and Replacing Missing Values
- Removing Duplicate Cases
- Rescaling a Variable
- Normalizing or Standardizing Data in a Data Frame
- Binning Numerical Data
- Creating Dummies for Categorical Variables
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What's in There? – Exploratory Data Analysis
- Creating Standard Data Summaries
- Extracting Subset of a Dataset
- Splitting a Dataset
- Creating Random Data Partitions
- Generating Standard Plots
- Generating Multiple Plots
- Selecting a Graphics Device
- Creating Plots with the Lattice and ggplot2package
- Creating Charts that Facilitate Comparisons
- Creating Charts that Visualize Possible Causality
- Creating Multivariate Plots
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Where Does It Belong? – Classification
- Generating Error/Classification-Confusion Matrices
- Generating ROC Charts
- Building, Plotting, and Evaluating – Classification Trees
- Using random Forest Models for Classification
- Classifying Using the Support Vector Machine Approach
- Classifying Using the Naïve Bayes Approach
- Classifying Using the KNN Approach
- Using Neural Networks for Classification
- Classifying Using Linear Discriminant Function Analysis
- Classifying Using Logistic Regression
- Using AdaBoost to Combine Classification Tree Models
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Give Me a Number – Regression
- Computing the Root Mean Squared Error
- Building KNN Models for Regression
- Performing Linear Regression
- Performing Variable Selection in Linear Regression
- Building Regression Trees
- Building Random Forest Models for Regression
- Using Neural Networks for Regression
- Performing k-Fold Cross-Validation and Leave-One-Out-Cross-Validation
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Can You Simplify That? – Data Reduction Techniques
Data analysis has recently emerged as a very important focus for a huge range of organizations and businesses. R makes detailed data analysis easier, making advanced data exploration and insight accessible to anyone interested in learning it. This video empowers you by showing you ways to use R to generate professional analysis reports. It provides examples for various important analysis and machine-learning tasks that you can try out with associated and readily available data. You will learn to carry out different tasks on the data to bring it into action.By the end of this course, you will be able to carry out different analyzing techniques, apply classification and regression, and also reduce data.
Style and Approach
This course follows a recipe-based approach. Here each video presents you with a step-by-step approach to performing many important data analytics tasks.
- Publication date:
- July 2017
- Publisher
- Packt
- Duration
- 3 hours 12 minutes
- ISBN
- 9781788390576