Machine Learning with R.
by Lantz, Brett
Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.
Read More ↓Title Statements
- Full title :Machine Learning with R.
Summary
Perhaps you already know a bit about machine learning but have never used R, or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.
Read More ↓Edition Statements
- Publication Date:©2015
- Edition:2nd ed
Publication Statements
- Publisher(s):Packt Publishing
- Place of Publication:Birmingham
- Language:eng
- Publication Date:©2015
Notes
Working with online data and services.
The Physical Object
- Description:1 online resource (452 pages)
Edition Identifiers
- ISBN:9781784394523, 1784394521
- oclc:on1058445191
- LC Classification:QA276.45.R3
- Dewey Decimal:005.8
Table of Contents
Cover -- Copyright -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Table of Contents -- Preface -- Chapter 1: Introducing Machine Learning -- The origins of machine learning -- Uses and abuses of machine learning -- Machine learning successes -- The limits of machine learning -- Machine learning ethics -- How machines learn -- Data storage -- Abstraction -- Generalization -- Evaluation -- Machine learning in practice -- Types of input data -- Types of machine learning algorithms -- Matching input data to algorithms -- Machine learning with R -- Installing R packages -- Loading and unloading R packages -- Summary -- Chapter 2: Managing and Understanding Data -- R data structures -- Vectors -- Factors -- Lists -- Data frames -- Matrixes and arrays -- Managing data with R -- Saving, loading, and removing R data structures -- Importing and saving data from CSV files -- Exploring and understanding data -- Exploring the structure of data -- Exploring numeric variables -- Measuring the central tendency -- mean and median -- Measuring spread -- quartiles and the five-number summary -- Visualizing numeric variables -- boxplots -- Visualizing numeric variables -…
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