Litgu.ru - Литературный Гуру

Название: Matters Computational
Автор: Jorg Arndt
Издательство: Springer
Год: 2011
Формат: pdf
Страниц: 978
Размер: 3,2 mb.
Язык: English

Este libro est? elaborado para todo aquel desarrollador interesado en los m?todos de computaci?n. Muchos de los conceptos aqu? expuestos, no suelen aparecer en los libros de texto o en aquellos dedicados a la algoritmia por lo que encontrarlos reunidos en un ?nico volumen puede resultar de gran ayuda tanto al estudiante como al profesional.

Название: Global Optimization Algorithms
Автор: Thomas Weise
Издательство: Autoedici?n
Год: 2009
Формат: pdf
Страниц: 820
Размер: 9,4 mb.
Язык: English

El objetivo de este libro es encontrar aquellas f?rmulas m?s ?ptimas para la optimizaci?n global de algoritmos a trav?s del perfil evolutivo.

Los algoritmos evolutivos son m?todos de optimizaci?n y b?squeda de soluciones basados en los postulados de la evoluci?n biol?gica. En ellos se mantiene un conjunto de entidades que representan posibles soluciones, las cuales se mezclan, y compiten entre s?, de tal manera que las m?s aptas son capaces de prevalecer a lo largo del tiempo, evolucionando hacia mejores soluciones cada vez.

Название: Essentials of Metaheuristics
Автор: Sean Luke
Издательство: George Mason University
Год: 2011
Формат: pdf
Страниц: 237
Размер: 4,2 mb.
Язык: English

Una metaheur?stica es un m?todo heur?stico para resolver un tipo de problema computacional general, usando los par?metros dados por el usuario sobre unos procedimientos gen?ricos y abstractos de una manera que se espera eficiente. Normalmente, estos procedimientos son heur?sticos. El nombre combina el prefijo griego "meta" ("m?s all?", aqu? con el sentido de "nivel superior") y "heur?stico"

Название: Data Structures and Algorithm Analysis. Java Version
Автор: Clifford A- Shaffer
Издательство: Autoedici?n
Год: 2012
Формат: pdf
Страниц: 601
Размер: 2,1 mb.
Язык: English

En programaci?n, una estructura de datos es una forma de organizar un conjunto de datos elementales con el objetivo de facilitar su manipulaci?n. Un dato elemental es la m?nima informaci?n que se tiene en un sistema.

Название: A Computer Science Tapestry
Автор: Owen L. Astrachan
Издательство: Duke University
Год: 1999
Формат: pdf
Страниц: 879
Размер: 3,8 mb.
Язык: English

Este libro es un libro de texto, no un libro de referencia: mientras que los libros de texto ense?an, el resto proporcionan un contenido donde resulta sencillo encontrar una respuesta r?pida a un problema puntual.

Название: The JHipster Mini-Book (Version 5.0.1)
Автор: Matt Raible
Издательство: InfoQ.com
Год: 2018
Язык: английский
Формат: epub
Размер: 15.7 MB

JHipster is one of those open-source projects you stumble upon and immediately think, “Of course!” It combines three very successful frameworks in web development: Bootstrap, Angular, and Spring Boot. This book shows you how to build an app with JHipster, and guides you through the plethora of tools, techniques, and options. Furthermore, it explains the UI components and API building blocks so you can understand the underpinnings of a JHipster application.

Название: Transforming the IT Services Lifecycle with AI Technologies
Автор: Kristof Kloeckner, John Davis
Издательство: Springer
Год: 2018
Язык: английский
Формат: pdf (true), epub
Размер: 19.2 MB

As more and more industries are experiencing digital disruption, using information technology to enable a competitive advantage becomes a critical success factor for all enterprises. This book will cover the authors' insights on how artificial intelligence (AI) technologies can fundamentally reshape the IT services delivery lifecycle to deliver better business outcomes through a data-driven and knowledge-based approach. Three main challenges and the technologies to address them are discussed in detail

Название: Extraction of Prosody for Automatic Speaker, Language, Emotion and Speech Recognition, 2nd Edition
Автор: Leena Mary
Издательство: Springer
Серия: SpringerBriefs in Speech Technology. Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning
Год: 2018 (2019 edition)
Язык: английский
Формат: pdf (true), epub
Размер: 10.17 MB

This updated book expands upon prosody for recognition applications of speech processing. It includes importance of prosody for speech processing applications; builds on why prosody needs to be incorporated in speech processing applications; and presents methods for extraction and representation of prosody for applications such as speaker recognition, language recognition and speech recognition. The updated book also includes information on the significance of prosody for emotion recognition and various prosody-based approaches for automatic emotion recognition from speech.

Название: Python: 21 Sample Codes And Advance Crash Course Guide In Python Programming
Автор: Zach Webber
Издательство: Independently published
ISBN: 1723976679
Год: 2018
Страниц: 82
Язык: английский
Формат: epub, pdf (conv)
Размер: 13.4 MB

So, you have learned the basics of Python and are ready to move on to the next level. You are hungry to learn what things are capable in Python and how to go about doing them. This book provides 21 coding examples, with explanations, and extra extensions you can complete. Though explanations are provided for all code samples, this book won’t hold your hand. It assumes you know a fair bit of Python conventions, but it also assumes you possess the programmer mindset and the ability to look at a code listing and know more or less what is happening. The code examples in this book vary in length from some 40 lines of code to over 200.

Название: Tree-Based Convolutional Neural Networks: Principles and Applications
Автор: Lili Mou, Zhi Jin
Издательство: Springer
ISBN: 9811318697
Год: 2018
Страниц: 104
Язык: английский
Формат: pdf (true), mobi, epub
Размер: 10.1 MB

In recent years, neural networks have become one of the most popular models in various applications of artificial intelligence, including image recognition, speech processing, and natural language processing. The convolutional neural network and the recurrent neural network are among the most popular neural architectures. The former uses a sliding window to capture translation invariant features; it typically works with signals in a certain dimensional space (e.g., 1D speech or 2D image). The latter is suitable to process time-series data as it iteratively aggregates information.