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Learning in Automated Manufacturing, Erwin Pesch


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Цена: 12157.00р.
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Автор: Erwin Pesch
Название:  Learning in Automated Manufacturing
ISBN: 9783790807929
Издательство: Springer
Классификация:



ISBN-10: 3790807923
Обложка/Формат: Paperback
Страницы: 257
Вес: 0.39 кг.
Дата издания: 30.08.1994
Серия: Production and Logistics
Язык: English
Размер: 234 x 156 x 15
Основная тема: Business and Management
Подзаголовок: A Local Search Approach
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Aims to acquaint the reader especially with the cases of local-search-based learning, as well as to introduce methods of constraint-based reasoning, both with respect to their use in automated manufacturing. Some design and planning issues in flexible manufacturing systems are also considered.


The Elements of Statistical Learning

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 10480.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 18622.00 р.
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Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning

Автор: Thorsten Wuest
Название: Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
ISBN: 3319176102 ISBN-13(EAN): 9783319176109
Издательство: Springer
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Цена: 19564.00 р.
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Описание: The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system.

Production Planning in Automated Manufacturing

Автор: Yves Crama; Alwin G. Oerlemans; Frits C.R. Spieksm
Название: Production Planning in Automated Manufacturing
ISBN: 3642802729 ISBN-13(EAN): 9783642802720
Издательство: Springer
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Цена: 15372.00 р.
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Описание: In this book quantitative approaches are proposed for production planning problems in automated manufacturing. The book will help to understand the nature of production planning problems in automated manufacturing and show how techniques from operations research may contribute to their solution.

Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning

Автор: Thorsten Wuest
Название: Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
ISBN: 3319386980 ISBN-13(EAN): 9783319386980
Издательство: Springer
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Цена: 14365.00 р.
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Описание: The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system.

Introduction to Manufacturing Processes

Автор: Groover
Название: Introduction to Manufacturing Processes
ISBN: 0470632283 ISBN-13(EAN): 9780470632284
Издательство: Wiley
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Цена: 30088.00 р.
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Описание: *Manufacturing Processes incorporates design topics, balance quantitative and qualitative coverage. The text also includes several case studies expanded upon online with related assessment content along with videos with related assessment questions.

Intelligent Data Engineering and Automated Learning – IDEAL 2015

Автор: Konrad Jackowski; Robert Burduk; Krzysztof Walkowi
Название: Intelligent Data Engineering and Automated Learning – IDEAL 2015
ISBN: 3319248332 ISBN-13(EAN): 9783319248332
Издательство: Springer
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Цена: 10062.00 р.
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Описание: Evolutionary algorithms.- Neural networks.- Probabilistic modeling.- Swarm intelligent, multi-objective optimization, and practical applications in regression.- Classification.- Clustering.-Biological data processing.- Text processing.- Video analysis.- Computational intelligence for optimization of communication networks.- Discovering knowledge from data.- Simulation-driven DES-like modeling and performance evaluation.- Intelligent applications in real-world problems.

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

Back to Basics Your Guide to Manufacturing Excellence

Название: Back to Basics Your Guide to Manufacturing Excellence
ISBN: 1574442791 ISBN-13(EAN): 9781574442793
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: Based on the popular "Back to Basics" columns that appear in the magazine "APICS: The Performance Advantage", this title details the key concepts necessary to expertly apply fresh approaches such as ERP, CPFR, and VMI. It includes topics such as: capacity, inventory, inventory accuracy, part numbering, processes, and problem solving.


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