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Computer and Information Science, Roger Lee


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Цена: 19564.00р.
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При оформлении заказа до: 2025-07-28
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Roger Lee
Название:  Computer and Information Science
ISBN: 9783319601694
Издательство: Springer
Классификация:



ISBN-10: 3319601695
Обложка/Формат: Hardcover
Страницы: 234
Вес: 0.53 кг.
Дата издания: 06.06.2017
Серия: Studies in Computational Intelligence
Язык: English
Издание: 1st ed. 2018
Иллюстрации: 50 illustrations, color; 46 illustrations, black and white; xiii, 234 p. 96 illus., 50 illus. in color.
Размер: 234 x 156 x 16
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book presents the edited proceedings of the 16th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2017), which was held on May 24-26, 2017 in Wuhan, China.


Computer Age Statistical Inference

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Emerging Trends and Applications in Cognitive Computing

Автор: MALLICK & BORAH
Название: Emerging Trends and Applications in Cognitive Computing
ISBN: 1522557938 ISBN-13(EAN): 9781522557937
Издательство: Mare Nostrum (Eurospan)
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Цена: 26961.00 р.
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Описание: Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making.Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.

Challenges and Applications for Implementing Machine Learning in Computer Vision

Автор: Ramgopal Kashyap, A.V. Senthil Kumar
Название: Challenges and Applications for Implementing Machine Learning in Computer Vision
ISBN: 1799801837 ISBN-13(EAN): 9781799801832
Издательство: Mare Nostrum (Eurospan)
Цена: 25978.00 р.
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Описание: Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.


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