The Essentials of Data Science Knowledge Discovery Using R 1st Edition by Graham Williams ISBN 1351647490 9781351647496

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Product details:

ISBN 10: 1351647490

ISBN 13: 9781351647496

Author: Graham J. Williams

The Essentials of Data Science: Knowledge Discovery Using R 1st Edition: 

 

The Essentials of Data Science: Knowledge Discovery Using R 1st Edition Table of contents:

1. Data Science
   1.1. Exercises

2. Introducing R
   2.1. Tooling for R Programming
   2.2. Packages and Libraries
   2.3. Functions, Commands, and Operators
   2.4. Pipes
   2.5. Getting Help
   2.6. Exercises

3. Data Wrangling
   3.1. Data Ingestion
   3.2. Data Review
   3.3. Data Cleaning
   3.4. Variable Roles
   3.5. Feature Selection
   3.6. Missing Data
   3.7. Feature Creation
   3.8. Preparing the Metadata
   3.9. Preparing for Model Building
   3.10. Save the Dataset
   3.11. A Template for Data Preparation
   3.12. Exercises

4. Visualising Data
   4.1. Preparing the Dataset
   4.2. Scatter Plot
   4.3. Bar Chart
   4.4. Saving Plots to File
   4.5. Adding Spice to the Bar Chart
   4.6. Alternative Bar Charts
   4.7. Box Plots
   4.8. Exercises

5. Case Study: Australian Ports
   5.1. Data Ingestion
   5.2. Bar Chart: Value/Weight of Sea Trade
   5.3. Scatter Plot: Throughput versus Annual Growth
   5.4. Combined Plots: Port Calls
   5.5. Further Plots
   5.6. Exercises

6. Case Study: Web Analytics
   6.1. Sourcing Data from CKAN
   6.2. Browser Data
   6.3. Entry Pages
   6.4. Exercises

7. A Pattern for Predictive Modelling
   7.1. Loading the Dataset
   7.2. Building a Decision Tree Model
   7.3. Model Performance
   7.4. Evaluating Model Generality
   7.5. Comparison of Performance Measures
   7.6. Save the Model to File
   7.7. A Template for Predictive Modelling
   7.8. Exercises

8. Ensemble of Predictive Models
   8.1. Loading the Dataset
   8.2. Random Forest
   8.3. Extreme Gradient Boosting
   8.4. Exercises

9. Writing Functions in R
   9.1. Model Evaluation
   9.2. Creating a Function
   9.3. Function for ROC Curves
   9.4. Exercises

10. Literate Data Science
    10.1. Basic LaTeX Template
    10.2. A Template for Our Narrative
    10.3. Including R Commands
    10.4. Inline R Code
    10.5. Formatting Tables Using Kable
    10.6. Formatting Tables Using XTable
    10.7. Including Figures
    10.8. Adding a Caption and Label
    10.9. Knitr Options
    10.10. Exercises

11. R with Style
    11.1. Why We Should Care
    11.2. Naming
    11.3. Comments
    11.4. Layout
    11.5. Functions
    11.6. Assignment
    11.7. Miscellaneous
    11.8. Exercises

 

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