Machine Learning Meets Medical Imaging, Kanwal Bhatia; Herve Lombaert
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: Kupinski, Ann Marie Название: Diagnostic Medical Sonography :Vascular Imaging ISBN: 1608313506 ISBN-13(EAN): 9781608313501 Издательство: Lippincott Williams & Wilkins Рейтинг: Цена: 13213.00 р. 18876.00-30% Наличие на складе: Есть (1 шт.) Описание: Lww'S Sonography Texts Are Up To Date With Technology, And The Needs Of Students And Faculty. Get The Right Content At The Right Level For The Right Way To Teach And Learn!Diagnostic Medical Sonography: Vascular Is The Most In-Depth, Appropriate Textbook To Cover This Type Of Ultrasound, And Is The Ideal Text For Sonography Students Pursuing A Greater Understanding Of This Specialization. Beginning With Core Anatomy Topics, This Text Is Aimed At Providing A Thorough Understanding Of This Crucial Topic, Giving It The Attention It Deserves, And Students And Faculty The Support They Want. As A Component Of The Diagnostic Medical Sonography Series, This Title Will Allow You To Provide A Comprehensive, Current, And Consistent Treatment Of Sonography Specializations In A Way You Were Never Able To Before.
Автор: Darren Cook Название: Practical Machine Learning with H2O ISBN: 149196460X ISBN-13(EAN): 9781491964606 Издательство: Wiley Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.
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.
Описание: Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum framework. Theoretical advances in quantum computing are hard to follow for computer scientists, and sometimes even for researchers involved in the field. The lack of a step-by-step guide hampers the broader understanding of this emergent interdisciplinary body of research. . Quantum Machine Learning sets the scene for a deeper understanding of the subject for readers of different backgrounds. The author has carefully constructed a clear comparison of classical learning algorithms and their quantum counterparts, thus making differences in computational complexity and learning performance apparent. This book synthesizes of a broad array of research into a manageable and concise presentation, with practical examples and applications.
Автор: Conway Drew, White John Myles Название: Machine Learning for Hackers ISBN: 1449303714 ISBN-13(EAN): 9781449303716 Издательство: Wiley Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within the reach any experienced programmer willing to crunch data.
Автор: Guorong Wu; Daoqiang Zhang; Luping Zhou Название: Machine Learning in Medical Imaging ISBN: 3319105809 ISBN-13(EAN): 9783319105802 Издательство: Springer Рейтинг: Цена: 7826.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Medical Imaging, MLMI 2014, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, in Cambridge, MA, USA, in September 2014.
Автор: Wu, Guorong Название: Machine Learning and Medical Imaging ISBN: 0128040769 ISBN-13(EAN): 9780128040768 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
Автор: Barber Название: Bayesian Reasoning and Machine Learning ISBN: 0521518148 ISBN-13(EAN): 9780521518147 Издательство: Cambridge Academ Рейтинг: Цена: 11088.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided. Additional resources available online and in the comprehensive software package include computer code, demos and teaching materials for instructors.
Автор: Bekkerman Название: Scaling up Machine Learning ISBN: 0521192242 ISBN-13(EAN): 9780521192248 Издательство: Cambridge Academ Рейтинг: Цена: 14731.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a variety of machine learning methods developed specifically for parallel or distributed systems, covering algorithms, platforms and applications.
Описание: This report documents current and ongoing developments in the area of learning in distributed artificial intelligence systems. The interdisciplinary co-operation of researchers from DAI and machine learning has established an active area of research and development.
Автор: Darby, M J; Barron, D; Hyland, R E Название: Oxford handbook of medical imaging ISBN: 0199216363 ISBN-13(EAN): 9780199216369 Издательство: Oxford Academ Рейтинг: Цена: 4750.00 р. Наличие на складе: Поставка под заказ.
Описание: A practical quick reference guide to the main techniques used to image common medical and surgical conditions.
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