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Artificial Intelligence Theory And Practice
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Book Synopsis Artificial Intelligence by : Thomas L. Dean
Download or read book Artificial Intelligence written by Thomas L. Dean and published by Addison-Wesley Professional. This book was released on 1995 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed understanding of the broad issues in artificial intelligence and a survey of current AI technology. The author delivers broad coverage of innovative representational techniques, including neural networks, image processing and probabilistic reasoning, alongside the traditional methods of symbolic reasoning. The work is intended for students in artificial intelligence, researchers and LISP programmers.
Book Synopsis Automated Planning by : Malik Ghallab
Download or read book Automated Planning written by Malik Ghallab and published by Elsevier. This book was released on 2004-05-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description
Book Synopsis Communicating Artificial Intelligence (AI) by : Seungahn Nah
Download or read book Communicating Artificial Intelligence (AI) written by Seungahn Nah and published by Routledge. This book was released on 2020-12-18 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite increasing scholarly attention to artificial intelligence (AI), studies at the intersection of AI and communication remain ripe for exploration, including investigations of the social, political, cultural, and ethical aspects of machine intelligence, interactions among agents, and social artifacts. This book tackles these unexplored research areas with special emphasis on conditions, components, and consequences of cognitive, attitudinal, affective, and behavioural dimensions toward communication and AI. In doing so, this book epitomizes communication, journalism and media scholarship on AI and its social, political, cultural, and ethical perspectives. Topics vary widely from interactions between humans and robots through news representation of AI and AI-based news credibility to privacy and value toward AI in the public sphere. Contributors from such countries as Brazil, Netherland, South Korea, Spain, and United States discuss important issues and challenges in AI and communication studies. The collection of chapters in the book considers implications for not only theoretical and methodological approaches, but policymakers and practitioners alike. The chapters in this book were originally published as a special issue of Communication Studies.
Book Synopsis Artificial Intelligence: Theory and Practice by : Thomas Dean
Download or read book Artificial Intelligence: Theory and Practice written by Thomas Dean and published by Turtleback Books. This book was released on 1994-12-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications by : Aboul Ella Hassanien
Download or read book Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-08-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.
Author :Piotr Buła Publisher :Routledge Studies in Innovation, Organizations and Technology ISBN 13 :9781032025834 Total Pages :0 pages Book Rating :4.0/5 (258 download)
Book Synopsis Management, Organisations and Artificial Intelligence by : Piotr Buła
Download or read book Management, Organisations and Artificial Intelligence written by Piotr Buła and published by Routledge Studies in Innovation, Organizations and Technology. This book was released on 2023-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines academic research with practical guidelines in methods and techniques to supplement existing knowledge relating to organizational management in the era of digital acceleration. It offers a simple layout with concise but rich content presented in an engaging, accessible style and the authors' holistic approach is unique in the field. From a universalist perspective, the book examines and analyzes the development of, among others, Industry 4.0, artificial intelligence (AI), AI 2.0, AI systems and platforms, algorithmics, new paradigms of organization management, business ecosystems, data processing models in AI-based organizations and AI strategies in the global perspective. An additional strength of the book is its relevance and contemporary nature, featuring information, data, forecasts or scenarios reaching up to 2030. How does one build, step by step, an organization that will be based on artificial intelligence technology and gain measurable benefits from it, for instance, as a result of its involvement in the creation of the so-called mesh ecosystem? The answer to this and many other pertinent questions are provided in this book. This timely and important book will appeal to scholars and students across the fields of organizational management and innovation and technology management, as well as managers, educators, scientists, entrepreneurs, innovators and more.
Book Synopsis Artificial Intelligence in Medical Imaging by : Lia Morra
Download or read book Artificial Intelligence in Medical Imaging written by Lia Morra and published by CRC Press. This book was released on 2019-11-25 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Choice Recommended Title, January 2021 This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective
Book Synopsis Artificial Intelligence and Machine Learning by : Lyla B. Das
Download or read book Artificial Intelligence and Machine Learning written by Lyla B. Das and published by I K International Pvt Ltd. This book was released on 2023-06-06 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for undergraduates, postgraduates and professionals who want to have a firm grip on the fundamental principles of AI and ML. Artificial Intelligence (AI) is a broad area of knowledge which has percolated into every aspect of human life. ‘Machine Learning algorithms’ are considered to be a subset of AI Theory, mathematics and coding are three aspects to any topic in AI. This book covers the most relevant topics in the field of Artificial Intelligence and Machine Learning (ML). The subdivisions of Machine Learning are Supervised, Unsupervised and Reinforcement learning. All three are covered in sufficient depth. One very important and upcoming field of application is Natural Language Processing (NLP). A whole section of the book has been devoted to this. The book covers the conceptual, mathematical and numerical analysis of the important ML algorithms and their practical applications. The topics covered include AI search algorithms, Classical machine learning, Deep learning theory and popular networks, Natural Language Processing (NLP) and Reinforcement learning. Numerical examples and lucid explanations give the reader an easy entry into the world of AI and ML.
Book Synopsis Machine Learning in Finance by : Matthew F. Dixon
Download or read book Machine Learning in Finance written by Matthew F. Dixon and published by Springer Nature. This book was released on 2020-07-01 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
Book Synopsis Machine Learning for Human Motion Analysis: Theory and Practice by : Wang, Liang
Download or read book Machine Learning for Human Motion Analysis: Theory and Practice written by Wang, Liang and published by IGI Global. This book was released on 2009-12-31 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book highlights the development of robust and effective vision-based motion understanding systems, addressing specific vision applications such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval"--Provided by publisher.
Book Synopsis Communicating Artificial Intelligence (AI) by : Seungahn Nah
Download or read book Communicating Artificial Intelligence (AI) written by Seungahn Nah and published by Routledge. This book was released on 2020-12-28 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite increasing scholarly attention to artificial intelligence (AI), studies at the intersection of AI and communication remain ripe for exploration, including investigations of the social, political, cultural, and ethical aspects of machine intelligence, interactions among agents, and social artifacts. This book tackles these unexplored research areas with special emphasis on conditions, components, and consequences of cognitive, attitudinal, affective, and behavioural dimensions toward communication and AI. In doing so, this book epitomizes communication, journalism and media scholarship on AI and its social, political, cultural, and ethical perspectives. Topics vary widely from interactions between humans and robots through news representation of AI and AI-based news credibility to privacy and value toward AI in the public sphere. Contributors from such countries as Brazil, Netherland, South Korea, Spain, and United States discuss important issues and challenges in AI and communication studies. The collection of chapters in the book considers implications for not only theoretical and methodological approaches, but policymakers and practitioners alike. The chapters in this book were originally published as a special issue of Communication Studies.
Book Synopsis Artificial Intelligence for Data Science in Theory and Practice by : Mohamed Alloghani
Download or read book Artificial Intelligence for Data Science in Theory and Practice written by Mohamed Alloghani and published by Springer Nature. This book was released on 2022-04-05 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides valuable information on effective, state-of-the-art techniques and approaches for governments, students, researchers, practitioners, entrepreneurs and teachers in the field of artificial intelligence (AI). The book explains the data and AI, types and properties of data, the relation between AI algorithms and data, what makes data AI ready, steps of data pre-processing, data quality, data storage and data platforms. Therefore, this book will be interested by AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.
Book Synopsis Artificial Intelligence in Behavioral and Mental Health Care by : David D. Luxton
Download or read book Artificial Intelligence in Behavioral and Mental Health Care written by David D. Luxton and published by Academic Press. This book was released on 2015-09-10 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Summarizes AI advances for use in mental health practice Includes advances in AI based decision-making and consultation Describes AI applications for assessment and treatment Details AI advances in robots for clinical settings Provides empirical data on clinical efficacy Explores practical issues of use in clinical settings
Book Synopsis Artificial Intelligence and Architecture by : Stanislas Chaillou
Download or read book Artificial Intelligence and Architecture written by Stanislas Chaillou and published by Birkhäuser. This book was released on 2022-03-07 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Künstliche Intelligenz (KI) hat Eingang in unzählige Branchen gefunden. In der Architektur steckt der Einsatz von KI noch in den Kinderschuhen, doch die Entwicklung der letzten Jahre hat vielversprechende Ergebnisse gebracht. Das Buch ist eine gut verständliche Einführung. Sie bietet einen Überblick über die Geschichte der KI und ihre ersten Anwendungen in der Architektur. Im zweiten Teil präsentiert der Autor konkrete Beispiele für den kreativen Einsatz von KI in der Praxis. Führende Experten, von der Havard-University bis zur Bauhaus Universität, eröffnen schließlich in Essays vielfältige Perspektiven auf das Potenzial von KI. Als Einführung zeigt das Buch ein Panorama dieser neuen technologischen Möglichkeiten und verdeutlicht so das Versprechen, das sie für die Architektur darstellen.
Book Synopsis Multiple Intelligences by : Howard E. Gardner
Download or read book Multiple Intelligences written by Howard E. Gardner and published by Basic Books. This book was released on 1993-04-20 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Howard Gardner's brilliant conception of individual competence is changing the face of education today. In the ten years since the publication of his seminal Frames of Mind , thousands of educators, parents, and researchers have explored the practical implications of Multiple Intelligences (MI) theory—the powerful notion that there are separate human capacities, ranging from musical intelligence to the intelligence involved in understanding oneself. Multiple Intelligences: The Theory in Practice brings together previously published and original work by Gardner and his colleagues at Project Zero to provide a coherent picture of what we have learned about the educational applications of MI theory from projects in schools and formal research over the last decade.
Book Synopsis Learning Deep Learning by : Magnus Ekman
Download or read book Learning Deep Learning written by Magnus Ekman and published by Addison-Wesley Professional. This book was released on 2021-07-19 with total page 1106 pages. Available in PDF, EPUB and Kindle. Book excerpt: NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience. After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus Ekman shows how to use them to build advanced architectures, including the Transformer. He describes how these concepts are used to build modern networks for computer vision and natural language processing (NLP), including Mask R-CNN, GPT, and BERT. And he explains how a natural language translator and a system generating natural language descriptions of images. Throughout, Ekman provides concise, well-annotated code examples using TensorFlow with Keras. Corresponding PyTorch examples are provided online, and the book thereby covers the two dominating Python libraries for DL used in industry and academia. He concludes with an introduction to neural architecture search (NAS), exploring important ethical issues and providing resources for further learning. Explore and master core concepts: perceptrons, gradient-based learning, sigmoid neurons, and back propagation See how DL frameworks make it easier to develop more complicated and useful neural networks Discover how convolutional neural networks (CNNs) revolutionize image classification and analysis Apply recurrent neural networks (RNNs) and long short-term memory (LSTM) to text and other variable-length sequences Master NLP with sequence-to-sequence networks and the Transformer architecture Build applications for natural language translation and image captioning NVIDIA's invention of the GPU sparked the PC gaming market. The company's pioneering work in accelerated computing--a supercharged form of computing at the intersection of computer graphics, high-performance computing, and AI--is reshaping trillion-dollar industries, such as transportation, healthcare, and manufacturing, and fueling the growth of many others. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Book Synopsis Forecasting with Artificial Intelligence by : Mohsen Hamoudia
Download or read book Forecasting with Artificial Intelligence written by Mohsen Hamoudia and published by Springer Nature. This book was released on 2023-10-22 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide that explores the intersection of artificial intelligence and forecasting, providing the latest insights and trends in this rapidly evolving field. The book contains fourteen chapters covering a wide range of topics, including the concept of AI, its impact on economic decision-making, traditional and machine learning-based forecasting methods, challenges in demand forecasting, global forecasting models, meta-learning and feature-based forecasting, ensembling, deep learning, scalability in industrial and optimization applications, and forecasting performance evaluation. With key illustrations, state-of-the-art implementations, best practices, and notable advances, this book offers practical insights into the theory and practice of AI-based forecasting. This book is a valuable resource for anyone involved in forecasting, including forecasters, statisticians, data scientists, business analysts, or decision-makers.
