The Essentials of Data Science: Knowledge Discovery Using R
Knowledge Discovery Using R
$325.50
- Hardcover
344 pages
- Release Date
13 July 2017
Summary
The Essentials of Data Science: Knowledge Discovery Using R presents the concepts of data science through a hands-on approach using free and open source software. It systematically drives an accessible journey through data analysis and machine learning to discover and share knowledge from data.
Building on over thirty years’ experience in teaching and practising data science, the author encourages a programming-by-example approach to ensure students and practitioners attune to the…
Book Details
| ISBN-13: | 9781498740005 |
|---|---|
| ISBN-10: | 1498740006 |
| Author: | Graham J. Williams |
| Publisher: | Taylor & Francis Inc |
| Imprint: | Chapman & Hall/CRC |
| Format: | Hardcover |
| Number of Pages: | 344 |
| Release Date: | 13 July 2017 |
| Weight: | 700g |
| Dimensions: | 156mm x 234mm |
| Series: | Chapman & Hall/CRC The R Series |
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Critics Review
“I have several books on data science and R, as well as other similar subjects and programming languages, in my personal library. However, this book is a great blend of important data science topics and R programming that will make it a great reference for anyone working in this important and immensely popular area. I highly recommend this book for college students learning what it takes to start their career in data science or even current professionals wanting to make a career change or who just want to know more about the subject (and do some R programming as well).”
~Dean V. Neubauer, Techometrics
“Due to the self-contained introduction to many of the features of R and RStudio, Graham J. Williams The Essentials of Data Science, Knowledge Discovery Using R would make an excellent recommended or supplementary text for a course that plans to use the rattle package. This book would also serve as a great resource for those with an interest in data science who would like a hands-on approach to learning R and gettting a flavor for a handful of topics within data science.”
~Katherine M. Kinnaird, Brown University
Graham J. Williams
Graham J. Williams is Director of Data Science with Microsoft and Honorary Associate Professor with the Australian National University. He is also Adjunct Professor with the University of Canberra. He was previously Senior Director of Analytics with the Australian Taxation Office, Lead Data Scientist with the Australian Government’s Centre of Excellence in Data Analytics, and International Visiting Professor of the Chinese Academy of Sciences.Over three decades , Graham has been an active machine learning researcher and author of many publications and software including Rattle. As a practitioner of data science he has deployed solutions in areas including finance, banking, insurance, health, education and government. He is also chair and steering committee member of international conferences in knowledge discovery, artificial intelligence, machine learning, and data mining.
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