IoT, Machine Learning and Data Analytics for Smart Healthcare, Azrour, Mourade ; Mabrouki, Jamal ; Guezzaz, Azidi
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 66520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Автор: Hemachandran K, Sayantan Khanra, Raul V. Rodriguez Название: Machine Learning for Business Analytics Real-Time Data Analysis for Decision-Making ISBN: 1032072814 ISBN-13(EAN): 9781032072814 Издательство: Taylor&Francis Рейтинг: Цена: 163330.00 T Наличие на складе: Нет в наличии. Описание: Machine Learning is an integral tool in a business analyst`s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable.
Автор: Dey, Nilanjan Название: Big Data Analytics for Intelligent Healthcare Management ISBN: 012818146X ISBN-13(EAN): 9780128181461 Издательство: Elsevier Science Рейтинг: Цена: 132500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data.
Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more
Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc.
Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more
Автор: El Morr Название: Machine Learning for Practical Decision Making ISBN: 3031169891 ISBN-13(EAN): 9783031169892 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science. It explains ML using simple language and a straightforward approach guided by real-world examples in areas such as health informatics, information technology, and business analytics. The book will help readers understand the various key algorithms, major software tools, and their applications. Moreover, through examples from the healthcare and business analytics fields, it demonstrates how and when ML can help them make better decisions in their disciplines. The book is chiefly intended for undergraduate and graduate students who are taking an introductory course in machine learning. It will also benefit data analysts and anyone interested in learning ML approaches.
Автор: Ghosh Название: Machine Intelligence and Data Analytics for Sustainable Future Smart Cities ISBN: 3030720675 ISBN-13(EAN): 9783030720674 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors.
Автор: Burk, Scott , Miner, Gary Название: It`s All Analytics! ISBN: 0367493799 ISBN-13(EAN): 9780367493790 Издательство: Taylor&Francis Рейтинг: Цена: 60220.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject.
Автор: Wang, Li & Perrizo Название: Big Data Analytics In Bioinformatics And Healthcare ISBN: 1466666110 ISBN-13(EAN): 9781466666115 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 247630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information.Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.
Название: Statistics and machine learning methods for ehr data ISBN: 0367442396 ISBN-13(EAN): 9780367442392 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data.
Автор: Jena Om Prakash, Bhushan Bharat, Kose Utku Название: Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications ISBN: 1032126876 ISBN-13(EAN): 9781032126876 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book incorporates the many facets of computational intelligence, such as machine learning and deep learning, to provide groundbreaking developments in healthcare applications. It discusses theory, analytical methods, numerical simulation, scientific techniques, analytical outcomes, and computational structuring.
Автор: Kumar Abhishek, Dubey Ashutosh Kumar, Anavatti Sreenatha G. Название: Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics ISBN: 0367676338 ISBN-13(EAN): 9780367676339 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In the last two decades, machine learning has been dramatically developed and is still experiencing a fast and ever-lasting change in paradigm, methodology, applications, and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on the diversity and complexity.
Название: Statistics and machine learning methods for ehr data ISBN: 0367638398 ISBN-13(EAN): 9780367638399 Издательство: Taylor&Francis Рейтинг: Цена: 45930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data.
