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Book Name: R for Data Science
Author: Garrett Grolemund, Hadley Wickham
ISBN-10: 1491910399
Year: 2017
Pages: 522
Language: English
File size: 32 MB
File format: PDF
Author: Garrett Grolemund, Hadley Wickham
ISBN-10: 1491910399
Year: 2017
Pages: 522
Language: English
File size: 32 MB
File format: PDF
R for Data Science Book Description:
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
This is a complete tutorial to learn data science and machine learning using R. By the end of this tutorial, you will have a good exposure to building predictive models using machine learning on your own. Note: No prior knowledge of data science / analytics is required. However, prior knowledge of algebra and statistics will be helpful.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
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You’ll learn how to:
Data Science Projects In R
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- Wrangle—transform your datasets into a form convenient for analysis
- Program—learn powerful R tools for solving data problems with greater clarity and ease
- Explore—examine your data, generate hypotheses, and quickly test them
- Model—provide a low-dimensional summary that captures true “signals” in your dataset
- Communicate—learn R Markdown for integrating prose, code, and results