CRCPress: New Books on Business Analytics, Graph Mining, Data Science

Latest books from CRC Press on important and relevant topics - Business Analytics, Intelligent Data Analysis, Graph Mining with R, and Data-Intensive Science. Special discount for KDnuggets readers.

Presenting New Titles from Chapman & Hall/CRC Press

Save 20% with Promo Code FVM30at

Getting Started with Business AnalyticsGetting Started with Business Analytics: Insightful Decision-Making,

David Roi Hardoon; Galit Shmueli

  • Explains the fundamentals of analytics methodologies and how they should be applied
  • Requires no prior knowledge of the subject
  • Defines and clarifies hyped buzzwords
  • Provides real-world examples of business analytics applications
  • Includes suggested business analytics projects
  • Offers supplementary resources at

Intelligent Data Analysis for Sustainable DevelopmentIntelligent Data Analysis for Sustainable Development

Editors: Ting Yu, Nitesh Chawla, and Simeon Simoff

  • Presents powerful techniques from mathematical optimization, data mining, machine learning, knowledge discovery, and other areas
  • Explains how these methods collect and analyze large quantities of environmental, economic, and social data, leading to better decision making for sustainable development
  • Focuses on spatiotemporal analysis for sustainable development applications
  • Explores the challenges involved with vast amounts of complex data
  • Includes real case studies on climate change, greenhouse gas emissions, renewable energy, smart grids, policy making, and more

Practical Graph Mining with RPractical Graph Mining with R

Editors: Nagiza F. Samatova, William Hendrix, John Jenkins, Kanchana Padmanabhan, Arpan Chakraborty

  • Focuses on approaches specifically for mining graph data, such as the use of graph kernels
  • Requires no prerequisites of mathematics or data mining
  • Provides numerous worked examples with R source code
  • Includes exercises and real-world applications at the end of each chapter
  • Solutions manual available upon qualifying course adoption

Data-Intensive ScienceData-Intensive Science

Editors: Terence Critchlow; Kerstin Kleese van Dam

  • Provides a comprehensive overview of how technical capabilities can be leveraged to enable scientific discovery
  • Offers a path forward for facilitating data-intensive science
  • Demonstrates the impact of data-intensive science through case studies highlighting current best practices

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