To see accurate pricing, please choose your delivery country.
 
 
United States
£ GBP
All Shops

British Wildlife

8 issues per year 84 pages per issue Subscription only

British Wildlife is the leading natural history magazine in the UK, providing essential reading for both enthusiast and professional naturalists and wildlife conservationists. Published eight times a year, British Wildlife bridges the gap between popular writing and scientific literature through a combination of long-form articles, regular columns and reports, book reviews and letters.

Subscriptions from £33 per year

Conservation Land Management

4 issues per year 44 pages per issue Subscription only

Conservation Land Management (CLM) is a quarterly magazine that is widely regarded as essential reading for all who are involved in land management for nature conservation, across the British Isles. CLM includes long-form articles, events listings, publication reviews, new product information and updates, reports of conferences and letters.

Subscriptions from £26 per year
Academic & Professional Books  Reference  Data Analysis & Modelling  Bioinformatics

The Essentials of Data Science Knowledge Discovery Using R

By: Graham J Williams(Author)
322 pages, colour illustrations
The Essentials of Data Science
Click to have a closer look
  • The Essentials of Data Science ISBN: 9781498740005 Hardback Jul 2017 Not in stock: Usually dispatched within 1 week
    £145.00
    #242289
Price: £145.00
About this book Contents Customer reviews Biography Related titles

About this book

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.

Contents

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

Customer Reviews

Biography

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.

By: Graham J Williams(Author)
322 pages, colour illustrations
Media reviews

"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

Current promotions
New and Forthcoming BooksNHBS Moth TrapBritish Wildlife MagazineBuyers Guides