Machine Learning and Knowledge Discovery in Databases, Annalisa Appice; Pedro Pereira Rodrigues; V?tor Sa
Автор: Kevin Murphy Название: Machine Learning ISBN: 0262018020 ISBN-13(EAN): 9780262018029 Издательство: MIT Press Рейтинг: Цена: 18622.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Wray Buntine; Marko Grobelnik; Dunja Mladenic; Joh Название: Machine Learning and Knowledge Discovery in Databases ISBN: 3642041736 ISBN-13(EAN): 9783642041730 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009.
Автор: Annalisa Appice; Pedro Pereira Rodrigues; V?tor Sa Название: Machine Learning and Knowledge Discovery in Databases ISBN: 3319235249 ISBN-13(EAN): 9783319235240 Издательство: Springer Рейтинг: Цена: 12298.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers.
Автор: Berendt Название: Machine Learning and Knowledge Discovery in Databases ISBN: 3319461303 ISBN-13(EAN): 9783319461304 Издательство: Springer Рейтинг: Цена: 8106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016.
Автор: Myra Spiliopoulou; Lars Schmidt-Thieme; Ruth Janni Название: Data Analysis, Machine Learning and Knowledge Discovery ISBN: 331901594X ISBN-13(EAN): 9783319015941 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics.
Автор: Animesh Adhikari; Jhimli Adhikari Название: Advances in Knowledge Discovery in Databases ISBN: 3319132113 ISBN-13(EAN): 9783319132112 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases.
Автор: Animesh Adhikari; Jhimli Adhikari Название: Advances in Knowledge Discovery in Databases ISBN: 3319366068 ISBN-13(EAN): 9783319366067 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases.
Автор: Albert Bifet; Michael May; Bianca Zadrozny; Ricard Название: Machine Learning and Knowledge Discovery in Databases ISBN: 3319234609 ISBN-13(EAN): 9783319234601 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers.
Автор: Walter Daelemans; Katharina Morik Название: Machine Learning and Knowledge Discovery in Databases ISBN: 3540874801 ISBN-13(EAN): 9783540874805 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covers the proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. This book addresses topics such as application of machine learning and data mining methods to real-world problems.
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.
Автор: Berthold Lausen; Sabine Krolak-Schwerdt; Matthias Название: Data Science, Learning by Latent Structures, and Knowledge Discovery ISBN: 366244982X ISBN-13(EAN): 9783662449820 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data;
Автор: Andreas Holzinger; Peter Kieseberg; A Min Tjoa; Ed Название: Machine Learning and Knowledge Extraction ISBN: 3319668072 ISBN-13(EAN): 9783319668079 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new edition of the best-selling book focuses on various aspects of recruiting, including assessing an institution`s readiness to recruit international students, building human resource capacity for international recruitment, creating an international recruitment plan, recruiting international students from within the United States, measuring return on investment, and more.
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