Probabilistic Data Structures and Algorithms for Big Data Applications

by Andrii Gakhov

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.

Genres: Programming, Computer Science, Nonfiction

220 pages, Paperback

Published August 5, 2022

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.

Reviews

[x · Rating 5 out of 5]

Very good book, with super important concepts explained clearly so that non-CompSci graduates like myself can clearly understand.

Recommended for any Data Scientists as it covers the underpinning algorithms and data structures that enable a lot of the big data work and analysis that is possible today.