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Modern Data Science with R

Af: Benjamin S. Baumer, Nicholas J. Horton, Daniel T. Kaplan Engelsk Hardback

Modern Data Science with R

Af: Benjamin S. Baumer, Nicholas J. Horton, Daniel T. Kaplan Engelsk Hardback
Tjek vores konkurrenters priser

From a review of the first edition: "Modern Data Science with R… is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician).

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions.

The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

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From a review of the first edition: "Modern Data Science with R… is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician).

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions.

The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 632
ISBN-13: 9780367191498
Indbinding: Hardback
Udgave: 2
ISBN-10: 0367191490
Kategori: Automatisk styrings- & reguleringsteknik
Udg. Dato: 14 apr 2021
Længde: 38mm
Bredde: 261mm
Højde: 183mm
Forlag: Taylor & Francis Ltd
Oplagsdato: 14 apr 2021
Forfatter(e): Benjamin S. Baumer, Nicholas J. Horton, Daniel T. Kaplan
Forfatter(e) Benjamin S. Baumer, Nicholas J. Horton, Daniel T. Kaplan

Kategori Automatisk styrings- & reguleringsteknik

ISBN-13 9780367191498

Sprog Engelsk

Indbinding Hardback

Sider 632

Udgave 2

Længde 38mm

Bredde 261mm

Højde 183mm

Udg. Dato 14 apr 2021

Oplagsdato 14 apr 2021

Forlag Taylor & Francis Ltd

Kategori sammenhænge