Human-Like Machine Intelligence, Muggleton, Stephen; Chater, Nicholas
Автор: Kevin Murphy Название: Machine Learning ISBN: 0262018020 ISBN-13(EAN): 9780262018029 Издательство: Random House (USA) Рейтинг: Цена: 17243.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Saifullah Khalid Название: Applications of Artificial Intelligence in Electrical Engineering ISBN: 1799827186 ISBN-13(EAN): 9781799827184 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 42451.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial intelligence is increasingly finding its way into industrial and manufacturing contexts. The prevalence of AI in industry from stock market trading to manufacturing makes it easy to forget how complex artificial intelligence has become. Engineering provides various current and prospective applications of these new and complex artificial intelligence technologies.
Applications of Artificial Intelligence in Electrical Engineering is a critical research book that examines the advancing developments in artificial intelligence with a focus on theory and research and their implications. Highlighting a wide range of topics such as evolutionary computing, image processing, and swarm intelligence, this book is essential for engineers, manufacturers, technology developers, IT specialists, managers, academicians, researchers, computer scientists, and students.
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
Описание: We are increasingly seeing computer systems which are expected to function without operator intervention. This is perhaps acceptable for running computer networks or traffic lights; however, we are now seeing computer systems deployed to qualitatively influence human judgments such as rulings on legal disputes or fitness for work to evaluate disability benefits. In keeping with the precautionary principle, it is important that those who are developing this capability - technologists and scientists - think through its potential implications.The aim of this book is to explore the technological and social and implications of computers and robots becoming increasingly 'aware' of their environment and the people in it, and their being increasingly 'self-aware' of their own existence within it.The wide-ranging scope of the text covers three different angles of the concept of 'the computer after me': (1) the next generation of computationally powerful aware systems; (2) systems in which the computer is aware of qualitatively impact human concerns such as law, health and rules; and (3) computers and robots which are aware of themselves.
Автор: Shi Zhongzhi Название: Mind Computation ISBN: 9813145803 ISBN-13(EAN): 9789813145801 Издательство: World Scientific Publishing Рейтинг: Цена: 24552.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Mind computation is a hot topic of intelligence science. It is explored by computing to explain the theoretical basis of human intelligence. Through long-term research, a mind model CAM (Consciousness and Memory) is proposed, which provides a general framework for brain-like intelligence and brain-like intelligent systems.
This novel book centers on mind model CAM, systematically discusses the theoretical basis of mind computation in nine chapters. Because of its advanced progresses on brain-like intelligence, it is useful as a primary reference volume for professionals and graduate students in intelligence science, cognitive science and artificial intelligence.
Описание: Garry Kasparov's 1997 chess match against the IBM supercomputer Deep Blue was a watershed moment in the history of technology. It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game. That moment was more than a century in the making, and in this breakthrough book, Kasparov reveals his astonishing side of the story for the first time. He describes how it felt to strategize against an implacable, untiring opponent with the whole world watching, and recounts the history of machine intelligence through the microcosm of chess, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition. Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. As many critics decry artificial intelligence as a menace, particularly to human jobs, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, rather than fear them. Deep Thinking is a tightly argued case for technological progress, from the man who stood at its precipice with his own career at stake.
Автор: Anderson Michael Название: Machine Ethics ISBN: 1108461751 ISBN-13(EAN): 9781108461757 Издательство: Cambridge Academ Рейтинг: Цена: 7762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The subject of this book is a new field of research: developing ethics for machines, in contrast to developing ethics for human beings who use machines. The essays in this volume represent the first steps by philosophers and artificial intelligence researchers toward explaining why it is necessary to add an ethical dimension to machines that function autonomously.
Описание: 1 Introduction1.1 Cyber-Physical Society1.2 Data1.2.1 General definition of data1.2.2 Data for computing1.2.3 The philosophy of between material and mind1.2.4 Views on Big Data1.2.5 Big networks of data and humans1.2.6 The shift of science paradigm1.2.7 The fourth industrial revolution1.2.8 Observed system, data, information, knowledge, humans and machines1.2.9 Problems2 Discovering Implicit Semantic Link in Cyber-Physical Society2.1 Semantic Link2.2 A brief history of Semantic Link Network2.3 Knowledge flowing through semantic links2.4 Modeling with local views and global views2.5 The Big Gap2.6 The Levels of Representation2.7 The semantic link networks that enable intelligence3 Dimensions on Data3.1 Different views of Dimension3.2 Dimensions on Big Data3.3 Multi-dimensional category space3.4 Complex multi-dimensional space and the tasks of analysis4 Multi-Dimensional Analytics4.1 Data operation dimension4.2 System behavior dimension4.3 Value dimension4.4 Time dimension4.5 Human dimension4.6 Strategic planning on multiple dimensions an example5 Unconventional Mapping from Data Space into Knowledge Space5.1 Mapping Representations into Wikipedia5.2 Mapping data space into knowledge space with cognition5.3 Mapping data into human-level concepts5.4 Mapping from representation into knowledge through complex modeling5.5 From correlation to knowledge5.6 Human representation and machine representation5.7 Knowledge flow through cognitive systems 6 Cyber-Physical-Social Infrastructure6.1 The development of Cyber-Infrastructure6.2 Big gaps between humans and machines 6.3 Incorporating cognitive architecture into cyber-infrastructure7 Communities of Cognition and Practice8 New Paradigm of Science8.1 The evolving paradigm of science8.2 Science process with data, concept, motivation, thinking, knowledge and interaction9 The Nature of Big Data Computing9.1 The computing nature 9.2 Problem-driven, data-driven, and data-based problem driven9.3 Beyond Turing test9.4 Analogical mapping 9.5 Toward an open interactive computing10 Mapping through Social Space11 The Emergence of Cyber-Physical-Social Intelligence11.1 Fundamental problem11.2 Methodology11.3 Understanding: extensible mapping from reality into mental space 11.4 Cyber-Physical-Social-Mental Computing11.5 Laws of the complex system12 Conclusion13 References
Автор: Alex Lui, Anna Farzinder, Mingboo Gong Название: Transforming Healthcare with Big Data and AI ISBN: 1641138971 ISBN-13(EAN): 9781641138970 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 7069.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field.
This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Поставка под заказ.
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.
Автор: Zhang Название: Toward Deep Neural Networks ISBN: 1138387037 ISBN-13(EAN): 9781138387034 Издательство: Taylor&Francis Рейтинг: Цена: 20671.00 р. Наличие на складе: Нет в наличии.
Описание: This book introduces deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors` 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet.
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