Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R
By: Lantz, Brett
Material type:
BookSeries: Publisher: Birmingham : Packt Publishing, c2015.Description: xiii, 426 p. : ill. ; 24 cm.ISBN: 9781784393908Program: CSCI323Subject(s): R (Computer program language) -- Handbooks, manuals, etc | Machine learning -- Statistical methods -- Handbooks, manuals, etc | COMPUTERS -- Machine Theory | COMPUTERS -- Programming Languages | Machine learning -- Statistical methods | R (Computer program language)DDC classification: 005.8 LA MA Online resources: Location Map
Summary:
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks. Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or.
| Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
| REGULAR | University of Wollongong in Dubai Main Collection | 005.8 LA MA (Browse shelf) | Available | T0053272 | ||
| REGULAR | University of Wollongong in Dubai Main Collection | 005.8 LA MA (Browse shelf) | Available | T0053273 |
Total holds: 0
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| 005.8 KO CY Cyberspace and cybersecurity / | 005.8 KO SH Shell programming in Unix, Linux and OS X | 005.8 LA MA Machine learning with R : | 005.8 LA MA Machine learning with R : | 005.8 LA NE Next generation wireless network security and privacy | 005.8 MA MO Modern cryptography : | 005.8 MA MO Modern cryptography : |
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks. Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or.
CSCI323