Название: Big CPU, Big Data
Автор: Alan Kaminsky
Издательство: Autoedici?n
Год: 2015
Формат: pdf
Страниц: 424
Размер: 11 mb.
Язык: English

To study parallel programming with this book, you’ll need the following prerequisite knowledge: Java programming; C programming (for GPU programs); computer organization concepts (CPU, memory, cache, and so on); operating system concepts (threads, thread synchronization).

Название: Algorithmics and Optimization
Автор: Andreas de Vries
Издательство: University of Applied Sciences of Hagen
Год: 2015
Формат: pdf
Страниц: 123
Размер: 1,24 mb.
Язык: English

Why mathematics in a book about algorithmics? Algorithms are, in essence, applied mathematics. Even if they deal with apparently “unmathematical” subjects such as manipulating strings or searching objects, mathematics is the basis. To mention just a few examples: the classical algorithmic concept of recursion is very closely related to the principle of mathematical induction; rigorous proofs are needed for establishing the correctness of given algorithms; running times have to be computed.

Название: Алгоритмы на Java
Автор: Роберт Седжвик, Кевин Уэйн
Издательство: Вильямс
Год: 2013
Страниц: 843
Формат: DJVU
Размер: 42 Мб
Язык: русский

В книге представлено исчерпывающее толкование структур данных и алгоритмов сортировки, поиска, обработки графов и строк, включая пятьдесят алгоритмов, которые должен знать каждый программист. Описываются новые реализации алгоритмов на Java, написанные в ясном модульном стиле, при котором весь код доступен читателю и полностью готов к использованию. В книге изучение алгоритмов на Java ведется в контексте важнейших научных, инженерных и коммерческих приложений.

Название: Lie Group Machine Learning
Автор: Fanzhang Li
Издательство: de Gruyter
Год: 2019
Страниц: 533
Формат: PDF
Размер: 14 Mb
Язык: English

This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advanced artifi cial intelligence. The book further discusses algorithms and applications in tensor learning, spectrum estimation learning, Finsler geometry learning, Homology boundary learning, and prototype theory.

Название: Синтез изображений. Базовые алгоритмы
Автор: Эгрон Ж.
Издательство: Радио и связь
ISBN: 5-256-00431-X
Год: 1993
Формат: PDF/DjVu
Страниц: 218
Размер: 38 MB
Язык: Русский

В книге французского специалиста собраны и систематизированы основные алгоритмы машинной графики, используемые при синтезе изображений с помощью ЭВМ. Описываются операции генерирования кривых, заполнения областей и взаимодействия геометрических объектов. Приведено около 50 программ, составленных на языке высокого уровня, что позволяет читателю воспользоваться готовой программой для конкретных условий. Автор ограничивается простейшим математическим аппаратом.

Название: Applied Scientific Computing: With Python
Автор: Peter R. Turner, Thomas Arildsen
Издательство: Springer
Серия: Texts in Computer Science
ISBN: 3319895745
Год: 2018
Страниц: 280
Язык: английский
Формат: pdf (true), epub
Размер: 15.2 MB

This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python.

Название: Modern Psychometrics with R
Автор: Patrick Mair
Издательство: Springer
Серия: Use R!
ISBN: 331993175X
Год: 2018
Страниц: 464
Язык: английский
Формат: pdf (true), epub
Размер: 43.7 MB

This textbook describes the broadening methodology spectrum of psychological measurement in order to meet the statistical needs of a modern psychologist. The way statistics is used, and maybe even perceived, in psychology has drastically changed over the last few years; computationally as well as methodologically. R has taken the field of psychology by storm, to the point that it can now safely be considered the lingua franca for statistical data analysis in psychology. The goal of this book is to give the reader a starting point when analyzing data using a particular method, including advanced versions, and to hopefully motivate him or her to delve deeper into additional literature on the method.

Название: Java XML and JSON: Document Processing for Java SE, 2nd Edition
Автор: Jeff Friesen
Издательство: Apress
Год: 2019
Страниц: 528
Формат: PDF, EPUB
Размер: 10 Mb
Язык: English

Use this guide to master the XML metalanguage and JSON data format along with significant Java APIs for parsing and creating XML and JSON documents from the Java language. New in this edition is coverage of Jackson (a JSON processor for Java) and Oracle’s own Java API for JSON processing (JSON-P), which is a JSON processing API for Java EE that also can be used with Java SE. This new edition of Java XML and JSON also expands coverage of DOM and XSLT to include additional API content and useful examples.

Название: Cryptography and Network Security: Principles and Practice, International Edition, 6 edition
Автор: William Stallings
Издательство: Pearson
Год: 2014
Формат: PDF
Размер: 12 Мб
Язык: английский / English

In this age of universal electronic connectivity, viruses and hackers, electronic eavesdropping, and electronic fraud, security is paramount. This text provides a practical survey of both the principles and practice of cryptography and network security. First, the basic issues to be addressed by a network security capability are explored through a tutorial and survey of cryptography and network security technology.

Название: Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Автор: Umberto Michelucci
Издательство: Apress
ISBN: 1484237897
Год: 2018
Страниц: 425
Язык: английский
Формат: pdf (true), epub
Размер: 30.0 MB

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish), seeing how to perform linear and logistic regression using TensorFlow, and choosing the right cost function.