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The second edition of this bestselling book provides an overview of the key topics in undergraduate mathematics, allowing beginning graduate... Læs mere
To succeed in data science you need some math proficiency. But not just any math. This common-sense guide provides a clear, plain English survey of the math you'll need... Læs mere
This new edition of Modern Fortran Explained provides a clear and thorough description of the latest version of Fortran, written by experts in the field with the intention that it remain the main reference work in the field.
Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative... Læs mere
This self-contained introduction to the Poisson process covers basic theory and certain advanced topics in the setting of a general abstract measure space. The text... Læs mere
This second edition explains how computer software is designed to perform the tasks required for sophisticated statistical analysis.
This graduate-level text covers theoretical and applied aspects of protecting digital data. Starting from the basics, it introduces error-correcting... Læs mere
Acta Numerica is an annual publication containing invited survey papers by leading researchers in numerical mathematics and scientific computing. The papers present overviews of recent developments in their area and provide state-of-the-art techniques and analysis.
Proof complexity is a rich subject drawing on methods from logic, combinatorics, algebra and computer science. This self-contained book presents the basic concepts, classical results,... Læs mere
Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This... Læs mere
The critical algorithms used in GIS are notoriously difficult to both teach and understand. This book address the problem by combining rigorous formal language with example case studies and student exercises.
With in-depth descriptions of data analysis techniques both for summarizing and correlation, the author's unconventional approach employs the concept of multivariate data summarization as an alternative to conventional machine-learning prediction methods.