Introduction to Data Science - Data Analysis and Prediction Algorithms with R (Hardcover)


Covers the basics of R and the tidyverse Demonstrate how to use ggplot2 to generate graphs and describe important Data Visualization principles Introduces Data Wranglin topics such as web scrapping, using regular expressions, and joining and reshaping data tables using the tidyverse tools Illustrates the importance of statistics in data analysis using case studies Uses the caret package to build prediction algorithms including K-nearest Neighbors and Random Forests Includes tools used on a day-to-day basis in data science projects including RStudio, UNIX/Linux shell, Git and GitHub, and knitr and R Markdown

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Product Description

Covers the basics of R and the tidyverse Demonstrate how to use ggplot2 to generate graphs and describe important Data Visualization principles Introduces Data Wranglin topics such as web scrapping, using regular expressions, and joining and reshaping data tables using the tidyverse tools Illustrates the importance of statistics in data analysis using case studies Uses the caret package to build prediction algorithms including K-nearest Neighbors and Random Forests Includes tools used on a day-to-day basis in data science projects including RStudio, UNIX/Linux shell, Git and GitHub, and knitr and R Markdown

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Product Details

General

Imprint

Crc Press

Country of origin

United Kingdom

Series

Chapman & Hall/CRC Data Science Series

Release date

November 2019

Availability

Expected to ship within 9 - 15 working days

First published

2020

Editors

Dimensions

254 x 178 x 43mm (L x W x T)

Format

Hardcover

Pages

713

ISBN-13

978-0-367-35798-6

Barcode

9780367357986

Categories

LSN

0-367-35798-4



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