Williams The Essentials of Data Science: Knowledge Discovery Using R

1. Auflage 2017
ISBN: 978-1-4987-4001-2
Verlag: CRC Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 344 Seiten

Reihe: Chapman & Hall/CRC The R Series

This book focuses is on data science. It includes plenty of actual examples of the typical data processing and data presentations required of a professional data scientist. The material will be especially useful to the growing profession of data scientists. As a practitioner, the author brings a practical view on the topic, with a very hands-on oriented presentation that will be particularly useful to other practitioners. The book also concentrates on the current generation of R packages that have added considerable capability to R, including Hadley Wickam's suite of packages, such as tidyr, dplyr, lubridate, stringr, and ggplot2.

Autoren/Hrsg.

Williams, Graham

Williams, Graham J.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie

Inhaltsverzeichnis

Part I - An Overview for the Data Scientist. Data Science, Analytics, and Data Mining. From Rattle to R for the Data Scientist. Preparing Data. Building Models. Case Studies. R Basics. Part II - Data Foundations. Reading Data into R. Exploring and Summarising Data. Transforming Data. Presenting Data. Part III - Analytics. Descriptive Analytics. Predictive Analytics. Prescriptive Analytics. Text Analytics. Social Network Analytics. Part IV - Advanced Data Science in R. Dealing with Big Data. Parallel Processing for High Performance Analytics. Ensembles for Big Data.

Über Autor(innen)

Dr Graham Williams is lead Data Scientist at the Australian Taxation Office, and was previously Principal Computer Scientist for Data Mining with CSIRO Australia. He is a Senior International Expert and Visiting Professor of the Chinese Academy of Sciences at the Shenzhen Institutes of Advanced Technologies. He is also Adjunct Professor, Data Mining, Fraud Prevention, Security, University of Canberra, and Australian National University.

Graham has been involved in data mining since the 1980s as a researcher and practitioner. He has lead projects with clients including the Health Insurance Commission, the Australian Taxation Office, the Commonwealth Bank, NRMA Insurance Limited, the Commonwealth Department of Health and Ageing, Queensland Health, and the Australian Customs Service. He has developed software and hardware environments for data mining, and implemented web services for the delivery of data mining. His research developments include Multiple (or Ensemble) Decision Tree Induction (1989), HotSpots for identifying target areas in very large data collections (1992), WebDM for the delivery of data mining services over the web using XML (1995), and Rattle (2005), a simple to use Graphical User Interface designed to make data mining accessible for data analysts. His popular text book on Data Mining with Rattle and R was published by Springer in 2011. His OnePageR website is an increasingly popular resource for data miners using R.