
Machine Learning with R
Expert techniques for predictive modeling
Brett Lantz(Author)
Packt Publishing
3rd Edition
Published on 15. April 2019
Book
Paperback/Softback
458 pages
978-1-78829-586-4 (ISBN)
Description
Solve real-world data problems with R and machine learning
Key Features
Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.6 and beyond
Harness the power of R to build flexible, effective, and transparent machine learning models
Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz
Book DescriptionMachine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.
Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings.
This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R.What you will learn
Discover the origins of machine learning and how exactly a computer learns by example
Prepare your data for machine learning work with the R programming language
Classify important outcomes using nearest neighbor and Bayesian methods
Predict future events using decision trees, rules, and support vector machines
Forecast numeric data and estimate financial values using regression methods
Model complex processes with artificial neural networks - the basis of deep learning
Avoid bias in machine learning models
Evaluate your models and improve their performance
Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow
Who this book is forData scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.
Key Features
Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.6 and beyond
Harness the power of R to build flexible, effective, and transparent machine learning models
Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz
Book DescriptionMachine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data.
Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings.
This new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R.What you will learn
Discover the origins of machine learning and how exactly a computer learns by example
Prepare your data for machine learning work with the R programming language
Classify important outcomes using nearest neighbor and Bayesian methods
Predict future events using decision trees, rules, and support vector machines
Forecast numeric data and estimate financial values using regression methods
Model complex processes with artificial neural networks - the basis of deep learning
Avoid bias in machine learning models
Evaluate your models and improve their performance
Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow
Who this book is forData scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.
More details
Edition
3rd Revised edition
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
Edition type
Revised edition
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 25 mm
Weight
849 gr
ISBN-13
978-1-78829-586-4 (9781788295864)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
06/2024
3rd Edition
Packt Publishing Limited
€36.99
Available for download
Person
Brett Lantz (DataSpelunking) has spent more than 10 years using innovative data methods to understand human behavior. A sociologist by training, Brett was first captivated by machine learning during research on a large database of teenagers' social network profiles. Brett is a DataCamp instructor and a frequent speaker at machine learning conferences and workshops around the world. He is known to geek out about data science applications for sports, autonomous vehicles, foreign language learning, and fashion, among many other subjects, and hopes to one day blog about these subjects at Data Spelunking, a website dedicated to sharing knowledge about the search for insight in data.
Content
Table of Contents
Introducing Machine Learning
Managing and Understanding Data
Lazy Learning
Probabilistic Learning
Divide and Conquer
Forecasting Numeric Data
Black Box Methods
Finding Patterns
Finding Groups of Data
Evaluating Model Performance
Improving Model Performance
Specialized Machine Learning Topics
Introducing Machine Learning
Managing and Understanding Data
Lazy Learning
Probabilistic Learning
Divide and Conquer
Forecasting Numeric Data
Black Box Methods
Finding Patterns
Finding Groups of Data
Evaluating Model Performance
Improving Model Performance
Specialized Machine Learning Topics