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Discrete Mathematics for Data Science provides an early course in both Data Science and Discrete Mathematics, focusing on how a deeper understanding of the former can unlock a more effective implementation of the latter.
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Discrete Mathematics for Data Science provides an early course in both Data Science and Discrete Mathematics, focusing on how a deeper understanding of the former can unlock a more effective implementation of the latter.
Bemærk: Kan ikke garanteres før jul. Se dato på varen.
Various aspects of graph theory find applications within the field of data science.In this book, the necessary foundations of abstract graph theory and linear algebra are covered in parallel, making it suitable for students in their early semesters.
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This edited volume presents advances in modeling and computational analysis techniques related to networks and online communities. This... Læs mere
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Finally, Part 4 goes into detail with recent and exciting new developments: dedicated studies designed... Læs mere
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This book is a timely collection of chapters that present the state of the art within the analysis and application of big data.
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This book reports on advanced concepts in fuzzy graph theory, showing a set of tools that can be successfully applied to understanding and modeling illegal human trafficking.
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This book bridges the gaps between logic, mathematics and computer science by delving into the theory of well-quasi orders, also known as wqos.
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This book bridges the gaps between logic, mathematics and computer science by delving into the theory of well-quasi orders, also known as wqos.
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Based on talks from the 2017 and 2018 Combinatorial and Additive Number Theory (CANT) workshops at the City University of New York, these proceedings offer 17 peer-reviewed and edited papers on current topics in number theory.