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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 1. R for Advanced Analytics

Note

Learning Objectives

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

  • Explain advanced R programming constructs

  • Print the summary statistics of a real-world dataset

  • Read data from CSV, text, and JSON files

  • Write R markdown files for code reproducibility

  • Explain R data structures such as data.frame, data.table, lists, arrays, and matrices

  • Implement the cbind, rbind, merge, reshape, aggregate, and apply functions

  • Use packages such as dplyr, plyr, caret, tm, and many more

  • Create visualizations using ggplot

Note

In this chapter, we will set the foundation for programming with R and understand the various syntax and data structures for advanced analytics.

You have been reading a chapter from
Applied Supervised Learning with R
Published in: May 2019
Publisher:
ISBN-13: 9781838556334
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