Cocaine cut with levamisole side effects. 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
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Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools. 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. For Data Science’ is a logical, contemporary entry point that compiles a relatively consisten t set of current R packages together in to a clean data science workflow appropriate for many purposes. This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides.
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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.
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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Data Science Using R
R For Data Science Book
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Data Science In R Pdf Books
- 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