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Applied Supervised Learning with R

You're reading from   Applied Supervised Learning with R Use machine learning libraries of R to build models that solve business problems and predict future trends

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Product type Paperback
Published in May 2019
Publisher
ISBN-13 9781838556334
Length 502 pages
Edition 1st Edition
Languages
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Authors (2):
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Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Karthik Ramasubramanian Karthik Ramasubramanian
Author Profile Icon Karthik Ramasubramanian
Karthik Ramasubramanian
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Toc

Table of Contents (12) Chapters Close

Applied Supervised Learning with R
Preface
1. R for Advanced Analytics FREE CHAPTER 2. Exploratory Analysis of Data 3. Introduction to Supervised Learning 4. Regression 5. Classification 6. Feature Selection and Dimensionality Reduction 7. Model Improvements 8. Model Deployment 9. Capstone Project - Based on Research Papers Appendix

Chapter 2. Exploratory Analysis of Data

Note

Learning Objectives

By the end of this chapter, you will be able to:

  • Define a problem statement with industry standard frameworks

  • Perform univariate and bivariate analysis

  • Explain multivariate analysis

  • Perform hypothesis testing

  • Perform data wrangling using the dplyr and reshape2 packages

  • Visualize data using the ggplot2 package

Note

In this chapter, we will acquaint learners with techniques to clean, transform, and visualize data in order to get useful insights.

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