It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise.

It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise.

This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows.It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R.

Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure.

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 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.

Brett Lantz 在应用创新的数据方法来理解人类的行为方面有10余年经验。他最初是一名社会学家，在学习一个青少年社交网站分布的大型数据库时，他就开始陶醉于机器学习。从那时起，他致力于移动电话、医疗账单数据和公益活动等交叉学科的研究，并维护dataspelunking.com这个网站，该网站致力于分享有关探寻数据中所蕴含的洞察的知识。 译者简介 李洪成　统计学博士，现为上海金融学院副教授，是SPSS统计分析软件和R语言专家。他的研究方向为金融统计和数据挖掘。他曾出版多本著作，并在专业杂志发表多篇论文，代表著作有《SPSS18数据分析基础与实践》、《SPSS数据分析教程》、《时间序列预测实践教程》，译著有《R语言经典实例》、《数据挖掘与R语言》、《金融数据分析导论：基于R语言》等。

Brett Lantz 在应用创新的数据方法来理解人类的行为方面有10余年经验。他最初是一名社会学家，在学习一个青少年社交网站分布的大型数据库时，他就开始陶醉于机器学习。从那时起，他致力于移动电话、医疗账单数据和公益活动等交叉学科的研究，并维护dataspelunking.com这个网站，该网站致力于分享有关探寻数据中所蕴含的洞察的知识。 译者简介 李洪成　统计学博士，现为上海金融学院副教授，是SPSS统计分析软件和R语言专家。他的研究方向为金融统计和数据挖掘。他曾出版多本著作，并在专业杂志发表多篇论文，代表著作有《SPSS18数据分析基础与实践》、《SPSS数据分析教程》、《时间序列预测实践教程》，译著有《R语言经典实例》、《数据挖掘与R语言》、《金融数据分析导论：基于R语言》等。

Machine 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 lan...(展开全部)

If you want to learn how to use R to build quantitative finance models with ease, this book is for you. Analysts who want to learn R to solve their quantitative finance problems will also find this book useful. Some understanding of the basic financial concepts will be useful, though prior knowledge of R is not required.

This book is for data science professionals, data analysts, or anyone with a working knowledge of machine learning, with R who now want to take their skills to the next level and become an expert in the field.