Introduction to data science [electronic resource] : data analysis and prediction algorithms with R / Rafael A. Irizarry.
"The book begins by going over the basics of R and the tidyverse. You learn R throughout the book, but in the first part we go over the building blocks needed to keep learning during the rest of the book"--
| Main Author: | |
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| Language: | English |
| Published: |
Boca Raton :
CRC Press, Taylor & Francis Group,
[2020]
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| Series: | CHAPMAN & HALL/CRC DATA SCIENCE SERIES
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| Subjects: | |
| Online Access: | |
| Variant Title: |
Introduction to Data Science: Data Analysis and Prediction Algorithms with R |
| Format: | Electronic eBook |
MARC
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| 020 | |z 9780367357986 | ||
| 020 | |z 9783319500164 | ||
| 020 | |a 9780429341830 (online) | ||
| 020 | |a 9781644642634 (online) | ||
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| 042 | |a pcc | ||
| 050 | 0 | 0 | |a QA276.45.R3 |
| 100 | 1 | |a Irizarry, Rafael A., |e author. | |
| 245 | 1 | 0 | |a Introduction to data science |h [electronic resource] : |b data analysis and prediction algorithms with R / |c Rafael A. Irizarry. |
| 246 | 2 | |a Introduction to Data Science: Data Analysis and Prediction Algorithms with R | |
| 264 | 1 | |a Boca Raton : |b CRC Press, Taylor & Francis Group, |c [2020] | |
| 490 | 0 | |a CHAPMAN & HALL/CRC DATA SCIENCE SERIES | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Installing R and RStudio -- Getting started with R and RStudio -- R Basics -- Programming basics -- The tidyverse -- Importing data -- Introduction to data visualization -- ggplot2 -- Visualizing data distributions -- Data visualization in practice -- Data visualization principles -- Robust summaries -- Introduction to statistics with R -- Probability -- Random variables -- Statistical inference -- Statistical models -- Regression -- Linear models -- Association is not causation -- Introduction to data wrangling -- Reshaping data -- Joining tables -- Web scraping -- String processing -- Parsing dates and times -- Text mining -- Introduction to machine learning -- Smoothing -- Cross validation -- The caret package -- Examples of algorithms -- Machine learning in practice -- Large datasets -- Clustering -- Introduction to productivty tools -- Accessing the terminal and installing Git -- Organizing with Unix -- Git and GitHub -- Reproducible projects with RStudio and R markdown. | |
| 520 | |a "The book begins by going over the basics of R and the tidyverse. You learn R throughout the book, but in the first part we go over the building blocks needed to keep learning during the rest of the book"-- |c Provided by publisher. | ||
| 650 | 0 | |a R (Computer program language) | |
| 650 | 0 | |a Information visualization. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Statistics |x Data processing. | |
| 650 | 0 | |a Probabilities |x Data processing. | |
| 650 | 0 | |a Computer algorithms. | |
| 650 | 0 | |a Quantitative research. | |
| 773 | 0 | |t Springer Computer Science eBooks 2017 English/International |d Springer Nature | |
| 776 | 0 | 8 | |i Print version: |a Irizarry, Rafael A.. |t Introduction to data science |d Boca Raton : CRC Press, Taylor & Francis Group, [2020] |z 9780367357986 |w (DLC) 2019025160 |
| 856 | 4 | 0 | |y Access Content Online(from Springer Computer Science eBooks 2017 English/International) |u https://ezproxy.msu.edu/login?url=https://link.springer.com/10.1007/978-3-319-50017-1 |z Springer Computer Science eBooks 2017 English/International: 2017 |