krainaksiazek a guide to graph colouring algorithms and applications 20096977

- znaleziono 6 produktów w 2 sklepach

A Guide to Graph Colouring - 2854483647

437,52 zł

A Guide to Graph Colouring Springer, Berlin

Książki / Literatura obcojęzyczna

This book addresses the graph colouring problem, focusing on state-of-the-art algorithms, and looking at how related structures can be exploited to produce high-performance heuristics algorithms. Topics and applications covered include operations research, metaheuristics, combinatorial optimization, and scheduling. The book will be of interest to researchers and graduate students in the areas of operations research, theoretical computer science, optimization, and computational intelligence.


Introduction to Graph Theory - 2854227115

271,68 zł

Introduction to Graph Theory PEARSON

Książki / Literatura obcojęzyczna

In recent years graph theory has emerged as a subject in its own right, as well as being an important mathematical tool in such diverse subjects as operational research, chemistry, sociology and genetics. Robin Wilson's book has been widely used as a text for undergraduate courses in mathematics, computer science and economics, and as a readable introduction to the subject for non-mathematicians. The opening chapters provide a basic foundation course, containing definitions and examples, connectedness, Eulerian and Hamiltonian paths and cycles, and trees, with a range of applications. This is followed by two chapters on planar graphs and colouring, with special reference to the four-colour theorem. The next chapter deals with transversal theory and connectivity, with applications to network flows. A final chapter on matroid theory ties together material from earlier chapters, and an appendix discusses algorithms and their efficiency.


Oxygen Forensic Detective (zawiera 12 m-cy aktualizacji) - 2833104000

34288,40 zł

Oxygen Forensic Detective (zawiera 12 m-cy aktualizacji) GSM-Support, Kraków

Oprogramowanie użytkowe > Oxygen > Programy dla śledczych

Oxygen Forensic Detective (zawiera 12 m-cy aktualizacji) - to oprogramowanie dla komputerów klasy PC służące do wydobycia maksymalnej ilości informacji z telefonów komórkowych i smartfonów, w celach dochodzeniowo-śledczych. Program ten odegrał znaczącą rolę w śledztwach w postępowaniach kryminalnych i innych w ponad 20 krajach na całym świecie. Jednym z głównych zastosowań tego oprogramowania jest odzyskiwanie informacji, które mogą służyć jako dowód w postępowaniu sądowym. Firma GSM-SUPPORT posiada bezpośrednią autoryzację od producenta na sprzedaż oprogramowania firmy Oxygen Software. Supports live data acquisition from 11,000+ mobile devices running on iOS, Android, Windows 8, Windows Mobile 5/6, RIM(Blackberry), Symbian, Bada, Chinese MTK chipset, and feature phones. Offers advanced Oxygen Forensic


Big Data Analytics with Spark - 2854441901

122,82 zł

Big Data Analytics with Spark Springer, Berlin

Książki / Literatura obcojęzyczna

Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis. You will learn how to use Spark for different types of big data analytics projects, including batch, interactive, graph, and stream data analysis as well as machine learning. In addition, this book will help you become a much sought-after Spark expert.§§Spark is one of the hottest Big Data technologies. The amount of data generated today by devices, applications and users is exploding. Therefore, there is a critical need for tools that can analyze large-scale data and unlock value from it. Spark is a powerful technology that meets that need. You can, for example, use Spark to perform low latency computations through the use of efficient caching and iterative algorithms; leverage the features of its shell for easy and interactive Data analysis; employ its fast batch processing and low latency features to process your real time data streams and so on. As a result, adoption of Spark is rapidly growing and is replacing Hadoop MapReduce as the technology of choice for big data analytics.§§This book provides an introduction to Spark and related big-data technologies. It covers Spark core and its add-on libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib. Big Data Analytics with Spark is therefore written for busy professionals who prefer learning a new technology from a consolidated source instead of spending countless hours on the Internet trying to pick bits and pieces from different sources.§The book also provides a chapter on Scala, the hottest functional programming language, and the program that underlies Spark. You'll learn the basics of functional programming in Scala, so that you can write Spark applications in it.§§What's more, Big Data Analytics with Spark provides an introduction to other big data technologies that are commonly used along with Spark, like Hive, Avro, Kafka and so on. So the book is self-sufficient; all the technologies that you need to know to use Spark are covered. The only thing that you are expected to know is programming in any language.§§There is a critical shortage of people with big data expertise, so companies are willing to pay top dollar for people with skills in areas like Spark and Scala. So reading this book and absorbing its principles will provide a boost - possibly a big boost - to your career.§§


Big Data Analytics Beyond Hadoop - 2854314887

292,61 zł

Big Data Analytics Beyond Hadoop PEARSON

Książki / Literatura obcojęzyczna

Master alternative Big Data technologies that can do what Hadoop can't: real-time analytics and iterative machine learning. When most technical professionals think of Big Data analytics today, they think of Hadoop. But there are many cutting-edge applications that Hadoop isn't well suited for, especially real-time analytics and contexts requiring the use of iterative machine learning algorithms. Fortunately, several powerful new technologies have been developed specifically for use cases such as these. Big Data Analytics Beyond Hadoop is the first guide specifically designed to help you take the next steps beyond Hadoop. Dr. Vijay Srinivas Agneeswaran introduces the breakthrough Berkeley Data Analysis Stack (BDAS) in detail, including its motivation, design, architecture, Mesos cluster management, performance, and more. He presents realistic use cases and up-to-date example code for: * Spark, the next generation in-memory computing technology from UC Berkeley * Storm, the parallel real-time Big Data analytics technology from Twitter * GraphLab, the next-generation graph processing paradigm from CMU and the University of Washington (with comparisons to alternatives such as Pregel and Piccolo) Halo also offers architectural and design guidance and code sketches for scaling machine learning algorithms to Big Data, and then realizing them in real-time. He concludes by previewing emerging trends, including real-time video analytics, SDNs, and even Big Data governance, security, and privacy issues. He identifies intriguing startups and new research possibilities, including BDAS extensions and cutting-edge model-driven analytics. Big Data Analytics Beyond Hadoop is an indispensable resource for everyone who wants to reach the cutting edge of Big Data analytics, and stay there: practitioners, architects, programmers, data scientists, researchers, startup entrepreneurs, and advanced students.


Data Science with Hadoop - 2826664413

146,22 zł

Data Science with Hadoop Pearson Education (US)

Książki / Literatura obcojęzyczna

As adoption of Hadoop accelerates in the enterprise and beyond, there's soaring demand for those who can solve real world problems by applying advanced data science techniques in Hadoop environments. Now there's a complete and up-to-date guide to data science with Hadoop: high-level concepts, deep-dive techniques, practical applications, hands-on tutorials, and real-world use cases. Drawing on their immense experience with Hadoop in enterprise Big Data environments, this book's authors bring together all the practical knowledge you'll need to do real, useful data science with Hadoop. Coverage includes: What data science is, what data scientists do, and how to build or join a data science team Core data science applications in retail, healthcare, insurance, banking, education, and beyond How Hadoop has evolved into an outstanding environment for doing data science A day in the life of a data scientist: exploration, iteration, and more Getting your data into Hadoop: data lakes, Sqoop, Flume, Falcon, and more Preparing your data, from start to finish Data modeling and machine learning Visualization: how (and how not) to use it Start-to-finish case studies: recommender systems, customer segmentation, sentiment analysis, and predictive risk modeling The future: Storm online scoring, GIRAPH graph algorithms, Solr/Elastic search, and more


Sklepy zlokalizowane w miastach: Warszawa, Kraków, Łódź, Wrocław, Poznań, Gdańsk, Szczecin, Bydgoszcz, Lublin, Katowice

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