Just enough R! :
Material type: TextPublication details: LONDON NEW YORK CRC PRESS 2020 Description: 1 online resource (xvii, 346 pages)ISBN: 9780367439149Subject(s): R (Computer program language) | Machine learning | Data structures (Computer science) | Mathematical statisticsDDC classification: 005.13/3 Summary: "Just Enough R! An Interactive Approach to Machine Learning and Analytics: presents just enough of the R language, machine learning algorithms, statistical methodology, and analytics for the reader to learn how to find interesting structure in data. The approach might be called "seeing then doing" as it first gives step by step explanations using simple, understandable examples of how the various machine learning algorithms work independent of any programming language. This is followed by detailed scripts written in R that apply the algorithms to solve nontrivial problems with real data. The script code is provided allowing the reader to execute the scripts as they study the explanations given in the text"--Item type | Current library | Call number | Status | Date due | Barcode |
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Books | Faculty of Science Library | QA276.45 .R63 2020 (Browse shelf(Opens below)) | Available | 0185183 |
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QA276.12 .A37 2009 Statistics: The Art and Science of Learning from Data | QA276.12 .K83 2004 Statistical Tutor - Elementary Statistics | QA276.2 .S64 2011 Statistics / | QA276.45 .R63 2020 Just enough R! : | QA303 .2 .H37 2007 University calculus / | QA303 .A34 2002 Elements of Calculus | QA303 .H35 2005 Calculus: Single Variable |
"A Chapman & Hall book."
"Just Enough R! An Interactive Approach to Machine Learning and Analytics: presents just enough of the R language, machine learning algorithms, statistical methodology, and analytics for the reader to learn how to find interesting structure in data. The approach might be called "seeing then doing" as it first gives step by step explanations using simple, understandable examples of how the various machine learning algorithms work independent of any programming language. This is followed by detailed scripts written in R that apply the algorithms to solve nontrivial problems with real data. The script code is provided allowing the reader to execute the scripts as they study the explanations given in the text"--
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