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Machine Learning for Signal Processing, Little Max A


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Цена: 80250.00T
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Автор: Little Max A   (Макс А. Литтл)
Название:  Machine Learning for Signal Processing
Перевод названия: Макс А. Литтл: Машинное обучение для обработки сигналов
ISBN: 9780198714934
Издательство: Oxford Academ
Классификация:



ISBN-10: 0198714939
Обложка/Формат: Hardcover
Страницы: 384
Вес: 0.38 кг.
Дата издания: 13.08.2019
Язык: English
Иллюстрации: 77 grayscale and 52 color line figures, 1 color halftone
Размер: 196 x 252 x 25
Читательская аудитория: General (us: trade)
Подзаголовок: Data science, algorithms, and computational statistics
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Pattern Recognition and Machine Learning

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
Рейтинг:
Цена: 79190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
Рейтинг:
Цена: 124150.00 T
Наличие на складе: Невозможна поставка.
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.


Kernel Methods and Machine Learning

Автор: Kung
Название: Kernel Methods and Machine Learning
ISBN: 110702496X ISBN-13(EAN): 9781107024960
Издательство: Cambridge Academ
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Цена: 90810.00 T
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Описание: Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred problems and real-world examples, it is an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors.

Predictive statistics

Автор: Clarke, Bertrand S. (university Of Nebraska, Lincoln) Clarke, Jennifer L. (university Of Nebraska, Lincoln)
Название: Predictive statistics
ISBN: 1107028280 ISBN-13(EAN): 9781107028289
Издательство: Cambridge Academ
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Цена: 83430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and `black box` settings, with computed examples.

Wireless AI: Wireless Sensing, Positioning, IoT, and Communications

Автор: K. J. Ray Liu, Beibei Wang
Название: Wireless AI: Wireless Sensing, Positioning, IoT, and Communications
ISBN: 1108497861 ISBN-13(EAN): 9781108497862
Издательство: Cambridge Academ
Рейтинг:
Цена: 121440.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A highly innovative and groundbreaking text explaining how wireless AI can be used to determine position, sense motion, and identity of objects and people. Covering theory, experimental results, and IoT applications, it is a must read for graduate students, researchers, and professionals working in signal processing and wireless communications.

Digital Signal Processing Using MATLAB

Автор: Schilling Robert J
Название: Digital Signal Processing Using MATLAB
ISBN: 1305636600 ISBN-13(EAN): 9781305636606
Издательство: Cengage Learning
Рейтинг:
Цена: 71800.00 T
Наличие на складе: Нет в наличии.
Описание: Focus on the development, implementation, and application of modern DSP techniques with DIGITAL SIGNAL PROCESSING USING MATLAB (R), 3E. Written in an engaging, informal style, this edition immediately captures your attention and encourages you to explore each critical topic. Every chapter starts with a motivational section that highlights practical examples and challenges that you can solve using techniques covered in the chapter.

Each chapter concludes with a detailed case study example, a chapter summary with learning outcomes, and practical homework problems cross-referenced to specific chapter sections for your convenience. DSP Companion software accompanies each book to enable further investigation. The DSP Companion software operates with MATLAB (R) and provides intriguing demonstrations as well as interactive explorations of analysis and design concepts.


Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 61750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
  • Includes open-access online courses that introduce practical applications of the material in the book

Cambridge Series in Statistical and Probabilistic Mathematic

Автор: Wainwright Martin J
Название: Cambridge Series in Statistical and Probabilistic Mathematic
ISBN: 1108498027 ISBN-13(EAN): 9781108498029
Издательство: Cambridge Academ
Рейтинг:
Цена: 71810.00 T
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Описание: Recent years have seen an explosion in the volume and variety of data collected in scientific disciplines from astronomy to genetics and industrial settings ranging from Amazon to Uber. This graduate text equips readers in statistics, machine learning, and related fields to understand, apply, and adapt modern methods suited to large-scale data.

Sensor Analysis for the Internet of Things

Автор: Michael Stanley, Jongmin Lee
Название: Sensor Analysis for the Internet of Things
ISBN: 1681732890 ISBN-13(EAN): 9781681732893
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 82230.00 T
Наличие на складе: Невозможна поставка.
Описание: While it may be attractive to view sensors as simple transducers which convert physical quantities into electrical signals, the truth of the matter is more complex. The engineer should have a proper understanding of the physics involved in the conversion process, including interactions with other measurable quantities. A deep understanding of these interactions can be leveraged to apply sensor fusion techniques to minimize noise and/or extract additional information from sensor signals.Advances in microcontroller and MEMS manufacturing, along with improved internet connectivity, have enabled cost-effective wearable and Internet of Things sensor applications. At the same time, machine learning techniques have gone mainstream, so that those same applications can now be more intelligent than ever before. This book explores these topics in the context of a small set of sensor types.We provide some basic understanding of sensor operation for accelerometers, magnetometers, gyroscopes, and pressure sensors. We show how information from these can be fused to provide estimates of orientation. Then we explore the topics of machine learning and sensor data analytics.

Adversarial Machine Learning

Автор: Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, J. D. Tygar
Название: Adversarial Machine Learning
ISBN: 1107043468 ISBN-13(EAN): 9781107043466
Издательство: Cambridge Academ
Рейтинг:
Цена: 83430.00 T
Наличие на складе: Невозможна поставка.
Описание: Combining essential theory and practical techniques for analysing system security, and building robust machine learning in adversarial environments, as well as including case studies on email spam and network security, this complete introduction is an invaluable resource for researchers, practitioners and students in computer security and machine learning.

Machine Learning

Автор: Flach
Название: Machine Learning
ISBN: 1107422221 ISBN-13(EAN): 9781107422223
Издательство: Cambridge Academ
Рейтинг:
Цена: 50680.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine Learning brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, the book explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.

The theory of quantum information

Автор: Watrous, John (university Of Waterloo, Ontario)
Название: The theory of quantum information
ISBN: 1107180562 ISBN-13(EAN): 9781107180567
Издательство: Cambridge Academ
Рейтинг:
Цена: 77090.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Intended for graduate students and researchers, this book presents a formal development of the mathematical theory of quantum information. Largely self-contained, with clear proofs and a wide range of exercises, it will help the reader grasp the fundamental facts and techniques that form the mathematical foundations of the subject.


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