The Essentials of Data Science: Knowledge Discovery Using R (Chapman & Hall/CRC: The R Series)
Language: English
Published by Chapman and Hall/CRC, 2017
- Softcover
- Used
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Condition: Used - Very good
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The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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- Title
- The Essentials of Data Science: Knowledge Discovery Using R (Chapman & Hall/CRC: The R Series)
- Author
- Williams, Graham J.
- Publisher
- Chapman and Hall/CRC
- Publication year
- 2017
- Condition
- Very Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1138088633
- ISBN 13
- 9781138088634
- Item weight
- 612 grams
- Series
- Book 32 of 73: Chapman & Hall/CRC The R
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 practise of data science while building their data skills. Proven frameworks are provided as reusable templates. Real world case studies then provide insight for the data scientist to swiftly adapt the templates to new tasks and datasets.
The book begins by introducing data science. It then reviews R’s capabilities for analysing data by writing computer programs. These programs are developed and explained step by step. From analysing and visualising data, the framework moves on to tried and tested machine learning techniques for predictive modelling and knowledge discovery. Literate programming and a consistent style are a focus throughout the book.
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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