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This book introduces readers to a workload-aware methodology for large-scale graph algorithm optimization in graph-computing systems, and proposes several optimization techniques that can enable these systems to handle advanced graph algorithms efficiently.
This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems.
Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: guides the... Læs mere
A Simple Guide to Technology and Analytics is a ready reference book for those times when you don’t really understand the technology and analytics being talked about.
Predator-prey interactions are ubiquitous, govern the flow of energy up trophic levels, and strongly influence the structure of... Læs mere
Explores the diverse applications of advanced tools and technologies of big data and its evidential value in business. It examines the role of... Læs mere
Support Vector Machines are now established as one of the standard tools for machine learning and data mining. Students... Læs mere
This novel book provides the reader with the fundamentals of data collection, model construction, analyses, and interpretation across a wide repertoire of demographic techniques and protocols, clearly guided throughout with fully reproducible R scripts.
Optimization techniques are at the core of data science. An understanding of the basic techniques and their fundamental properties provides important grounding for... Læs mere
The book is intended for practitioners in data science and data analytics in both academic and business environments. It aims to present the reader with concepts in data science and analytics that were deemed to be more advanced or simply out of scope in the author's first book.