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 Название: Pyomo - Optimization Modeling in Python, 3rd Edition
Автор: Michael L. Bynum, Gabriel A. Hackebeil, William E. Hart, Carl D. Laird, Bethany L. Nicholson, John D. Siirola, Jean-Paul Watson, David L. Woodruff
Издательство: Springer
Год: 2021
Формат: PDF
Страниц: 242
Размер: 13 Mb
Язык: English
This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models. The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. | |
Разместил: vitvikvas 31-03-2021, 10:02 | Комментарии: 0 | Подробнее
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 Название: Thinking Machines: Machine Learning and Its Hardware Implementation
Автор: Shigeyuki Takano
Издательство: Academic Press
Год: 2021
Формат: PDF
Страниц: 324
Размер: 16 Mb
Язык: English
Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks.
This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning. | |
Разместил: vitvikvas 31-03-2021, 08:21 | Комментарии: 0 | Подробнее
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 Название: Машинное обучение на R: экспертные техники для прогностического анализа
Автор: Бретт Ланц
Язык: русский
Издательство: Питер
Год: 2020
Страниц: 464
Формат: pdf
Размер: 19,3 Мб
Язык R предлагает мощный набор методов машинного обучения, позволяющих быстро проводить нетривиальный анализ ваших данных. Книга является руководством, которое поможет применять методы машинного обучения в решении ежедневных задач. Бретт Ланц научит всему необходимому для анализа данных, формирования прогнозов и визуализации данных. Здесь вы найдете информацию о новых улучшенных библиотеках, советы об этических аспектах машинного обучения и проблемах предвзятости, а также познакомитесь с глубоким обучением.
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Разместил: PRESSI 31-03-2021, 08:01 | Комментарии: 0 | Подробнее
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 Название: Simulink 3D Animation User's Guide (R2021a)
Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: 2021
Страниц: 452
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Visualize dynamic system behavior in a virtual reality environment. Simulink® 3D Animation links Simulink models and MATLAB algorithms to 3D graphics objects in virtual reality scenes. You can animate a virtual world by changing position, rotation, scale, and other object properties during desktop or real-time simulation. You can also sense collisions and other events in the virtual world and feed them back into your MATLAB and Simulink algorithms. Video from virtual cameras can be streamed to Simulink for processing. | |
Разместил: Ingvar16 30-03-2021, 17:18 | Комментарии: 0 | Подробнее
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 Название: Структуры данных и проектирование программ
Автор: Круз Р.Л.
Издательство: Лаборатория знаний
Год: 2017 - 3-е изд.
Cтраниц: 768
Формат: pdf (ocr)
Размер: 22 мб
Язык: русский
В качестве фундаментальных средств разработки программ рассматриваются такие вопросы, как структурное решение задач, абстракция данных, принципы программной инженерии и сравнительный анализ алгоритмов. Дано полное освещение большинства модулей знаний, касающихся структур данных и алгоритмов. Большая часть глав начинается основной темой и сопровождается примерами, приложениями и практическими исследованиями. Это учебное пособие дает основательные знания, которые позволяют студентам по ходу своей дальнейшей работы использовать ее также в качестве справочного пособия. | |
Разместил: rivasss 30-03-2021, 11:42 | Комментарии: 0 | Подробнее
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 Название: Python for MBAs
Автор: Mattan Griffel, Daniel Guetta
Издательство: Columbia University Press
Год: 2021
Формат: True PDF
Страниц: 368
Размер: 12 Mb
Язык: English
From the ads that track us to the maps that guide us, the twenty-first century runs on code. The business world is no different. Programming has become one of the fastest-growing topics at business schools around the world. An increasing number of MBAs are choosing to pursue careers in tech. For them and other professionals, having some basic coding knowledge is a must.rogramming language. | |
Разместил: bomboane 30-03-2021, 10:06 | Комментарии: 0 | Подробнее
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 Название: Recognition and Perception of Images: Fundamentals and Applications
Автор: Scrivener Publishing LLC
Издательство:
Год: 2021
Формат: True PDF
Страниц: 474
Размер: 95.9 Mb
Язык: English
This book is dedicated to the unique interdisciplinary research of imagery processing, recognition and perception. The contents of this book are based on the concepts of mathematical processing, compositional analysis applied in the art and design, and psychological factors of the information perception process. | |
Разместил: bomboane 30-03-2021, 09:56 | Комментарии: 0 | Подробнее
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 Название: Machine Reading Comprehension: Algorithms and Practice
Автор: Chenguang Zhu
Издательство: Elsevier Inc
Год: 2021
Формат: true pdf/epub/azw3
Страниц: 272
Размер: 12.6 Mb
Язык: English
Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. | |
Разместил: bomboane 30-03-2021, 09:46 | Комментарии: 0 | Подробнее
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 Название: The Blockchain Technology for Secure and Smart Applications across Industry Verticals (Advances in Computers, Volume 121)
Автор: Neeraj Kumar (Editor), Shubhani Aggarwal (Editor), Pethuru Raj (Editor)
Издательство: Elsevier Inc
Год: 2021
Формат: True PDF
Страниц: 517
Размер: 54 Mb
Язык: English
The Blockchain Technology for Secure and Smart Applications across Industry Verticals, Volume 121, presents the latest information on a type of distributed ledger used for maintaining a permanent and tamper-proof record of transactional data. The book presents a novel compendium of existing and budding Blockchain technologies for various smart applications. Chapters in this new release include the Basics of Blockchain, The Blockchain History, Architecture of Blockchain, Core components of Blockchain, Blockchain 2.0: Smart Contracts, Empowering Digital Twins with Blockchain, Industrial Use Cases at the Cusp of the IoT and Blockchain Paradigms, Blockchain Components and Concepts, Digital Signatures, Accumulators, Financial Systems, and more. | |
Разместил: bomboane 30-03-2021, 09:12 | Комментарии: 0 | Подробнее
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 Название: Graph Representation Learning
Автор: William L. Hamilton
Издательство: Morgan & Claypool
Серия: Synthesis Lectures on Artificial Intelligence and Machine Learning
Год: 2020
Страниц: 161
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into Deep Learning (DL) architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. Machine Learning (ML) is inherently a problem-driven discipline. | |
Разместил: Ingvar16 29-03-2021, 20:21 | Комментарии: 0 | Подробнее
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