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Data Analytics & Visualization All-in-One For Dummies
book

Data Analytics & Visualization All-in-One For Dummies

by Jack A. Hyman, Luca Massaron, Paul McFedries, John Paul Mueller, Lillian Pierson, Jonathan Reichental, Joseph Schmuller, Alan R. Simon, Allen G. Taylor
April 2024
Beginner content levelBeginner
832 pages
20h 32m
English
For Dummies
Content preview from Data Analytics & Visualization All-in-One For Dummies

Chapter 1

Using Open Source R for Data Science

IN THIS CHAPTER

Bullet Exploring R programming

Bullet Previewing popular R packages

Bullet Playing with more advanced R packages

Data science involves the skillful application of math, coding, and subject matter expertise in ways that allow data scientists to generate reliable and accurate predictions from data. While the last element — subject matter expertise — is unique to each practitioner, if you apply data science within a business context, then you’d want to make sure you’ve got a good handle on the needed business acumen and the math-and-statistics requirements of data science (Book 1, Chapter 3). Another important data science constituent to consider is coding, which can be done using the open source programming language R, as covered in this chapter, or Python (covered in Book 6).

This chapter describes the fundamental concepts of programming with R (such as data types, functions, and classes). The machine learning models you build with R or Python can serve as the decision engines within AI SaaS products you build for your company. The chapter also introduces some of the best R packages for manipulating data, performing statistical computations, ...

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Publisher Resources

ISBN: 9781394244096Purchase Link