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Artificial Intelligence and Machine Learning Powered Public Service Delivery in Estonia, Martin Ebers, Paloma Kroot Tupay


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Автор: Martin Ebers, Paloma Kroot Tupay   (Мартин Эберс)
Название:  Artificial Intelligence and Machine Learning Powered Public Service Delivery in Estonia
Перевод названия: Мартин Эберс: Предоставление государственных услуг на основе искусственного интеллекта и машинного о
ISBN: 9783031196669
Издательство: Springer
Классификация:




ISBN-10: 303119666X
Обложка/Формат: Hardback
Страницы: 237
Вес: 0.56 кг.
Дата издания: 29.01.2023
Серия: Data Science, Machine Intelligence, and Law
Язык: English
Издание: 1st ed. 2023
Иллюстрации: Xxi, 237 p.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Law
Подзаголовок: Opportunities and legal challenges
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book gives a comprehensive overview of the state of Artificial Intelligence (AI), especially machine learning (ML) applications in public service delivery in Estonia, discussing the manifold ethical and legal issues that arise under both European and Estonian law. Final conclusions and recommendations set out and analyze various policy options for the public sector, taking into account recent developments at the European level – such as the AIA proposal – as well as the experience of countries that have issued principles and guidelines or even laws for the use of ML in the public sector. “For two reasons, this study is relevant not only for an audience which is interested in Estonian administrative law. First, the authors base their legal analysis primarily on EU law and provide a state of the art-analysis of the relevant secondary legislation. This makes the book a reference text for the European debate on public sector AI governance. Second, this study is part of a larger research project in which four specific use cases of public sector AI have been developed and tested. The practical insights gained in these projects have provided the authors with an excellent understanding of the opportunities and risks of the technology, which distinguishes this legal analysis from similar enterprises.” Excerpt from the foreword by Professor Thomas Wischmeyer (University of Bielefeld)
Дополнительное описание: 1. Introduction.- 2. The Promise and Perils of AI and ML in Public Administration.- 3.The Regulatory Framework in Overview.- 4. Privacy Issues: Processing Personal Data, Monitoring, and Profiling Citizens.- 5. Delegation of Administrative Powers to AI Sys



Applications of artificial intelligence (AI) and machine learning (ML) in the petroleum industry /

Автор: Shah, Manan
Название: Applications of artificial intelligence (AI) and machine learning (ML) in the petroleum industry /
ISBN: 1032245654 ISBN-13(EAN): 9781032245652
Издательство: Taylor&Francis
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Цена: 13779.00 р.
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Описание: The book explores the variety of applications that can be integrated to support the existing petroleum and adjacent sectors to solve industry problems, serving as a useful guide for professionals working in the petroleum industry, industrial engineers, artificial intelligence and machine learning experts and researchers, as well as students.

We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law

Автор: Chesterman Simon
Название: We, the Robots?: Regulating Artificial Intelligence and the Limits of the Law
ISBN: 1316517683 ISBN-13(EAN): 9781316517680
Издательство: Cambridge Academ
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Цена: 5702.00 р.
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Описание: Should we regulate artificial intelligence? Can we? From self-driving cars and high-speed trading to algorithmic decision-making, the way we live, work, and play is increasingly dependent on AI systems. This book examines how our laws are dealing with AI, as well as what additional rules and institutions are needed.

Neural Network Methods in Natural Language Processing

Автор: Goldberg Yoav
Название: Neural Network Methods in Natural Language Processing
ISBN: 1627052984 ISBN-13(EAN): 9781627052986
Издательство: Mare Nostrum (Eurospan)
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Цена: 11504.00 р.
Наличие на складе: Нет в наличии.

Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Artificial Intelligence In Healthcare

Автор: Bohr, Adam
Название: Artificial Intelligence In Healthcare
ISBN: 0128184388 ISBN-13(EAN): 9780128184387
Издательство: Elsevier Science
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Цена: 16505.00 р.
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Описание:

Artificial Intelligence in Healthcare Data is more than a comprehensive introduction to artificial intelligence and machine learning. The book is split into two sections with an introduction to current healthcare data challenges that is followed by specific applications and case studies. The editors explore how AI is used as a tool in the analysis of healthcare data, specifically focusing on machine learning, deep learning, natural language processing. data privacy, cybersecurity and the ethics. Other sections explore how AI tools can help to interrogate data across a range of healthcare applications, including AI driven wearables and sensors and AI assisted surgery.

This book will be useful for researchers, graduate students and practitioners in computer science, data science, bioinformatics, health informatics, biomedical engineering and clinical engineering.

Artificial Intelligence in Behavioral and Mental Health Care

Автор: David D. Luxton
Название: Artificial Intelligence in Behavioral and Mental Health Care
ISBN: 0124202489 ISBN-13(EAN): 9780124202481
Издательство: Elsevier Science
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Цена: 9262.00 р.
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Описание:

Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy.

In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering.

This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source.

Machine Learning for IOS Developers

Автор: Mishra Abhishek
Название: Machine Learning for IOS Developers
ISBN: 1119602874 ISBN-13(EAN): 9781119602873
Издательство: Wiley
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Цена: 6018.00 р.
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Описание:

Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner

Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple's ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications.

Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book's clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models--both pre-trained and user-built--with Apple's CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers:

  • Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics
  • Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming
  • Develop skills in data acquisition and modeling, classification, and regression.
  • Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS)
  • Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreML

Machine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.

Machine Learning for Future Wireless Communications

Автор: Fa–Long Luo
Название: Machine Learning for Future Wireless Communications
ISBN: 1119562252 ISBN-13(EAN): 9781119562252
Издательство: Wiley
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Цена: 18683.00 р.
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Описание:

A comprehensive review to the theory, application and research of machine learning for future wireless communications

In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities.

Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author - a noted expert on the topic - covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource:

  • Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks
  • Covers a range of topics from architecture and optimization to adaptive resource allocations
  • Reviews state-of-the-art machine learning based solutions for network coverage
  • Includes an overview of the applications of machine learning algorithms in future wireless networks
  • Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing

Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Principles of Quantum Artificial Intelligence (Second Edition): Quantum Problem Solving and Machine Learning

Автор: Wichert Andreas Miroslaus
Название: Principles of Quantum Artificial Intelligence (Second Edition): Quantum Problem Solving and Machine Learning
ISBN: 9811224307 ISBN-13(EAN): 9789811224300
Издательство: World Scientific Publishing
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Цена: 24552.00 р.
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Описание:

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making -- the core disciplines of artificial intelligence.

Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds

Lean AI: How Innovative Startups Use Artificial Intelligence to Grow

Автор: Patel Lomit
Название: Lean AI: How Innovative Startups Use Artificial Intelligence to Grow
ISBN: 1492059315 ISBN-13(EAN): 9781492059318
Издательство: Wiley
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Цена: 6334.00 р.
Наличие на складе: Поставка под заказ.

Описание: With this practical book, author Lomit Patel shows you how to use AI and automation to provide an operational layer atop those acquisition solutions to deliver amazing results for your company.

Artificial Intelligence in a Throughput Model

Автор: Rodgers, Waymond
Название: Artificial Intelligence in a Throughput Model
ISBN: 0367217813 ISBN-13(EAN): 9780367217815
Издательство: Taylor&Francis
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Цена: 26796.00 р.
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Описание: This book provides an overview of the existing biometric technologies, decision-making algorithms and the growth opportunity in biometrics. The book proposes a throughput model, which draws on computer science, economics and psychology to model perceptual, informational sources, judgmental processes and decision choice algorithms.

Artificial Intelligence in a Throughput Model

Автор: Rodgers, Waymond
Название: Artificial Intelligence in a Throughput Model
ISBN: 0367507463 ISBN-13(EAN): 9780367507466
Издательство: Taylor&Francis
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Цена: 11023.00 р.
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Описание: This book provides an overview of the existing biometric technologies, decision-making algorithms and the growth opportunity in biometrics. The book proposes a throughput model, which draws on computer science, economics and psychology to model perceptual, informational sources, judgmental processes and decision choice algorithms.

Artificial intelligence and machine learning in business management :

Автор: Sandeep Kumar Panda
Название: Artificial intelligence and machine learning in business management :
ISBN: 0367645556 ISBN-13(EAN): 9780367645557
Издательство: Taylor&Francis
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Цена: 17609.00 р.
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Описание: The focus of this book is to introduce Artificial Intelligence (AI) and Machine Learning (ML) technologies into the context of Business Management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers.


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