nach der Bestellung gedruckt Neuware - Printed after ordering - A technical book about popular space-efficient data structures and fast algorithms that are extremely useful in modern Big Data applications.The purpose of this book is to introduce technology practitioners, including software architects and developers, as well as technology decision makers to probabilistic data structures and algorithms. Reading this book, you will get a theoretical and practical understanding of probabilistic data structures and learn about their common uses.

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Bibliographic Details

Title: Probabilistic Data Structures and Algorithms for Big Data Applications
Publisher: Bod - Books On Demand, Bod - Books On Demand
Publication Date: 2022
Language: English
ISBN 10: 3748190484
ISBN 13: 9783748190486
Binding: Taschenbuch
Condition: Neu
Dimensions: 220 millimeters width by 155 millimeters height by 16 millimeters depth
Weight: 360 grams

About this title

Synopsis

A technical book about popular space-efficient data structures and fast algorithms that are extremely useful in modern Big Data applications. The purpose of this book is to introduce technology practitioners, including software architects and developers, as well as technology decision makers to probabilistic data structures and algorithms. Reading this book, you will get a theoretical and practical understanding of probabilistic data structures and learn about their common uses.

About the Author

Andrii Gakhov is a mathematician and software engineer holding a Ph.D. in mathematical modeling and numerical methods. He has been a teacher in the School of Computer Science at V. Karazin Kharkiv National University in Ukraine for a number of years and currently works as a software practitioner for ferret go GmbH, the leading community moderation, automation, and analytics company in Germany. His fields of interests include machine learning, stream mining, and data analysis.

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