System Design for Epidemics Using Machine Learning and Deep Learning, Kanagachidambaresan
Автор: Bonaccorso Giuseppe Название: Hands-On Unsupervised Learning with Python ISBN: 1789348277 ISBN-13(EAN): 9781789348279 Издательство: Неизвестно Рейтинг: Цена: 9562.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Unsupervised learning is a key required block in both machine learning and deep learning domains. You will explore how to make your models learn, grow, change, and develop by themselves whenever they are exposed to a new set of data. With this book, you will learn the art of unsupervised learning for different real-world challenges.
Автор: Fandango Armando Название: Mastering TensorFlow ISBN: 1788292065 ISBN-13(EAN): 9781788292061 Издательство: Неизвестно Рейтинг: Цена: 7171.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: We cover advanced deep learning concepts (such as transfer learning, generative adversarial models, and reinforcement learning), and implement them using TensorFlow and Keras. We cover how to build and deploy at scale with distributed models. You will learn to build TensorFlow models using R, Keras, TensorFlow Learn, TensorFlow Slim and Sonnet
Описание: This book equips readers with the knowledge to data analytics, machine learning and deep learning techniques for applications defined under the umbrella of Industry 4.0.
Автор: Subasi, Abdulhamit Название: Practical Machine Learning For Data Analysis Using Python ISBN: 0128213795 ISBN-13(EAN): 9780128213797 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
Название: Machine-to-Machine Communications ISBN: 1466561238 ISBN-13(EAN): 9781466561236 Издательство: Taylor&Francis Рейтинг: Цена: 20671.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
With the number of machine-to-machine (M2M)-enabled devices projected to reach 20 to 50 billion by 2020, there is a critical need to understand the demands imposed by such systems. Machine-to-Machine Communications: Architectures, Technology, Standards, and Applications offers rigorous treatment of the many facets of M2M communication, including its integration with current technology.
Presenting the work of a different group of international experts in each chapter, the book begins by supplying an overview of M2M technology. It considers proposed standards, cutting-edge applications, architectures, and traffic modeling and includes case studies that highlight the differences between traditional and M2M communications technology.
Details a practical scheme for the forward error correction code design
Investigates the effectiveness of the IEEE 802.15.4 low data rate wireless personal area network standard for use in M2M communications
Identifies algorithms that will ensure functionality, performance, reliability, and security of M2M systems
Illustrates the relationship between M2M systems and the smart power grid
Presents techniques to ensure integration with and adaptation of existing communication systems to carry M2M traffic
Providing authoritative insights into the technologies that enable M2M communications, the book discusses the challenges posed by the use of M2M communications in the smart grid from the aspect of security and proposes an efficient intrusion detection system to deal with a number of possible attacks. After reading this book, you will develop the understanding required to solve problems related to the design, deployment, and operation of M2M communications networks and systems.
Автор: Guo, Song (the Hong Kong Polytechnic University) Qu, Zhihao (the Hong Kong Polytechnic University) Название: Edge learning for distributed big data analytics ISBN: 1108832377 ISBN-13(EAN): 9781108832373 Издательство: Cambridge Academ Рейтинг: Цена: 9502.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field.
Автор: Garg Lalit, Chakraborty Chinmay, Mahmoudi Saпd Название: Healthcare Informatics for Fighting Covid-19 and Future Epidemics ISBN: 3030727513 ISBN-13(EAN): 9783030727512 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents innovative solutions utilising informatics to deal with various issues related to the COVID-19 outbreak.
Описание: This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems.
Описание: Machine learning allows models or systems to learn without being explicitly programmed. You will see how to use the best of libraries support such as scikit-learn, Tensorflow and much more to build efficient smart systems.
Описание: You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.
Описание: This book uses real-life datasets from Kaggle to explain basic statistics for machine learning for data segmentation, regression predictions, and forecasts. You`ll focus on variable dependency and autocorrelation to build, test, and use a linear regression prediction model and time series forecasts.
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