Описание: This book describes active illumination techniques in computer vision. The final part shows how such active illumination techniques can be applied to various domains, describing the issue to be overcome by active illumination techniques and the advantages of using these techniques.
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: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Автор: Tor Lattimore, Csaba Szepesvari Название: Bandit Algorithms ISBN: 1108486827 ISBN-13(EAN): 9781108486828 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for graduate students interested in exploring stochastic, adversarial and Bayesian frameworks.
Автор: Fabio Manganiello Название: Computer Vision with Maker Tech ISBN: 1484268202 ISBN-13(EAN): 9781484268209 Издательство: Springer Рейтинг: Цена: 7317.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Harness the untapped potential of combining a decentralized Internet of Things (IoT) with the ability to make predictions on real-world fuzzy data. This book covers the theory behind machine learning models and shows you how to program and assemble a voice-controlled security. You'll learn the differences between supervised and unsupervised learning and how the nuts-and-bolts of a neural network actually work.
You'll also learn to identify and measure the metrics that tell how well your classifier is doing. An overview of other types of machine learning techniques, such as genetic algorithms, reinforcement learning, support vector machines, and anomaly detectors will get you up and running with a familiarity of basic machine learning concepts. Chapters focus on the best practices to build models that can actually scale and are flexible enough to be embedded in multiple applications and easily reusable.
With those concepts covered, you'll dive into the tools for setting up a network to collect and process the data points to be fed to our models by using some of the ubiquitous and cheap pieces of hardware that make up today's home automation and IoT industry, such as the RaspberryPi, Arduino, ESP8266, etc. Finally, you'll put things together and work through a couple of practical examples. You'll deploy models for detecting the presence of people in your house, and anomaly detectors that inform you if some sensors have measured something unusual.
And you'll add a voice assistant that uses your own model to recognize your voice. What You'll LearnDevelop a voice assistant to control your IoT devicesImplement Computer Vision to detect changes in an environmentGo beyond simple projects to also gain a grounding machine learning in generalSee how IoT can become "smarter" with the inception of machine learning techniquesBuild machine learning models using TensorFlow and OpenCVWho This Book Is ForMakers and amateur programmers interested in taking simple IoT projects to the next level using TensorFlow and machine learning. Also more advanced programmers wanting an easy on ramp to machine learning concepts.
Автор: Shinichi Nakajima, Kazuho Watanabe, Masashi Sugiyama Название: Variational Bayesian Learning Theory ISBN: 1107076153 ISBN-13(EAN): 9781107076150 Издательство: Cambridge Academ Рейтинг: Цена: 20275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designed for researchers and graduate students in machine learning, this book introduces the theory of variational Bayesian learning, a popular machine learning method, and suggests how to make use of it in practice. Detailed derivations allow readers to follow along without prior knowledge of the specific mathematical techniques.
Автор: Moitra, Ankur (massachusetts Institute Of Technology) Название: Algorithmic aspects of machine learning ISBN: 1107184584 ISBN-13(EAN): 9781107184589 Издательство: Cambridge Academ Рейтинг: Цена: 10613.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is reshaping our everyday life. This book explores the theoretical underpinnings in an accessible way, offering theoretical computer scientists an introduction to important models and problems and offering machine learning researchers a cutting-edge algorithmic toolkit.
Автор: Moitra Ankur Название: Algorithmic Aspects of Machine Learning ISBN: 1316636003 ISBN-13(EAN): 9781316636008 Издательство: Cambridge Academ Рейтинг: Цена: 5386.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is reshaping our everyday life. This book explores the theoretical underpinnings in an accessible way, offering theoretical computer scientists an introduction to important models and problems and offering machine learning researchers a cutting-edge algorithmic toolkit.
Автор: Sugiyama, Masashi (tokyo Institute Of Technology) Suzuki, Taiji (university Of Tokyo) Kanamori, Takafumi (nagoya University, Japan) Название: Density ratio estimation in machine learning ISBN: 1108461735 ISBN-13(EAN): 9781108461733 Издательство: Cambridge Academ Рейтинг: Цена: 6018.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. The book introduces theories, methods and applications of density ratio estimation. This is the first and definitive treatment of the entire framework of density ratio estimation.
Название: Scaling up machine learning ISBN: 1108461743 ISBN-13(EAN): 9781108461740 Издательство: Cambridge Academ Рейтинг: Цена: 7445.00 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.
Автор: Roberto Cipolla; Sebastiano Battiato; Giovanni Mar Название: Machine Learning for Computer Vision ISBN: 3642446868 ISBN-13(EAN): 9783642446863 Издательство: Springer Рейтинг: Цена: 14817.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Collecting articles covering talks and tutorials from the latest session of the International Computer Vision Summer School (ICVSS), this book offers a thorough exploration of current progress in the science and technology of making machines that see.
Описание: examines the effective features that characterize static hand poses and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition and a novel hand segmentation and gesture recognition system.
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