Technical Abstract Bulletin
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Publisher :
Page : 196 pages
File Size : 42,94 MB
Release : 1981
Category : Science
ISBN :
Author :
Publisher :
Page : 196 pages
File Size : 42,94 MB
Release : 1981
Category : Science
ISBN :
Author :
Publisher :
Page : 622 pages
File Size : 21,25 MB
Release : 1981
Category : Computer programming
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Page : 1112 pages
File Size : 18,90 MB
Release : 1982
Category : Science
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Author :
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Page : 636 pages
File Size : 34,47 MB
Release : 1981
Category : Transportation
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Page : 942 pages
File Size : 47,87 MB
Release : 1981
Category : Government reports announcements & index
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Author : University of California, Berkeley. Institute of Transportation Studies. Library
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Page : 66 pages
File Size : 27,30 MB
Release : 1982
Category : Transportation
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Page : 410 pages
File Size : 10,96 MB
Release : 1982
Category : Public administration
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Page : 112 pages
File Size : 35,41 MB
Release : 1989-08-28
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New York magazine was born in 1968 after a run as an insert of the New York Herald Tribune and quickly made a place for itself as the trusted resource for readers across the country. With award-winning writing and photography covering everything from politics and food to theater and fashion, the magazine's consistent mission has been to reflect back to its audience the energy and excitement of the city itself, while celebrating New York as both a place and an idea.
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Page : 2012 pages
File Size : 32,77 MB
Release : 2006
Category : Indexes
ISBN :
Author : Hadley Wickham
Publisher : "O'Reilly Media, Inc."
Page : 521 pages
File Size : 16,1 MB
Release : 2016-12-12
Category : Computers
ISBN : 1491910364
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. You'll learn how to: 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