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Machine Understanding
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Book Synopsis Machine Understanding by : Zbigniew Les
Download or read book Machine Understanding written by Zbigniew Les and published by Springer. This book was released on 2019-08-01 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book discusses machine understanding (MU). This new branch of classic machine perception research focuses on perception that leads to understanding and is based on the categories of sensory objects. In this approach the visual and non-visual knowledge, in the form of visual and non-visual concepts, is used in the complex reasoning process that leads to understanding. The book presents selected new concepts, such as perceptual transformations, within the machine understanding framework, and uses perceptual transformations to solve perceptual problems (visual intelligence tests) during understanding, where understanding is regarded as an ability to solve complex visual problems described in the authors’ previous books. Thanks to the uniqueness of the research topics covered, the book appeals to researchers from a wide range of disciplines, especially computer science, cognitive science and philosophy.
Book Synopsis Understanding Machine Learning by : Shai Shalev-Shwartz
Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Book Synopsis Understanding Machine Understanding by : Ken Clements
Download or read book Understanding Machine Understanding written by Ken Clements and published by Universal-Publishers. This book was released on 2024-10-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive and thought-provoking exploration of the nature of machine understanding, its evaluation, and its implications. The book proposes a new framework, the Multifaceted Understanding Test Tool (MUTT), for assessing machine understanding across multiple dimensions, from language comprehension and logical reasoning to social intelligence and metacognition. Through a combination of philosophical analysis, technical exposition, and narrative thought experiments, the book delves into the frontiers of machine understanding, raising fundamental questions about the cognitive mechanisms and representations that enable genuine understanding in both human and machine minds. By probing the boundaries of artificial comprehension, the book aims to advance our theoretical grasp on the elusive notion of understanding and inform responsible development and deployment of AI technologies. In an era where Artificial Intelligence systems are becoming integral to our daily lives, a pressing question arises: Do these machines truly understand what they are doing, or are they merely sophisticated pattern matchers? "Understanding Machine Understanding" delves into this profound inquiry, exploring the depths of machine cognition and the essence of comprehension. Join Ken Clements and Claude 3 Opus on an intellectual journey that challenges conventional benchmarks like the Turing Test and introduces the innovative Multifaceted Understanding Test Tool (MUTT). This groundbreaking framework assesses AI's capabilities across language, reasoning, perception, and social intelligence, aiming to distinguish genuine understanding from mere imitation. Through philosophical analysis, technical exposition, and engaging narratives, this book invites readers to explore the frontiers of AI comprehension. Whether you're an AI researcher, philosopher, or curious observer, "Understanding Machine Understanding" offers a thought-provoking guide to the future of human-machine collaboration. Discover what it truly means for a machine to understand--and the implications for our shared future.
Book Synopsis Interpretable Machine Learning by : Christoph Molnar
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Book Synopsis Shape Understanding System by : Zbigniew Les
Download or read book Shape Understanding System written by Zbigniew Les and published by Springer. This book was released on 2015-02-06 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the third book presenting selected results of research on the further development of the shape understanding system (SUS) carried out by authors in the newly founded Queen Jadwiga Research Institute of Understanding. In this book the new term Machine Understanding is introduced referring to a new area of research aiming to investigate the possibility of building machines with the ability to understand. It is presented that SUS needs to some extent mimic human understanding and for this reason machines are evaluated according to the rules applied for the evaluation of human understanding. The book shows how to formulate problems and how it can be tested if the machine is able to solve these problems.
Book Synopsis Shape Understanding System – Knowledge Implementation and Learning by : Zbigniew Les
Download or read book Shape Understanding System – Knowledge Implementation and Learning written by Zbigniew Les and published by Springer. This book was released on 2012-07-27 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the selected results of research on the further development of the shape understanding system (SUS) described in our previous book titled “Shape Understanding System: the First Steps Toward the Visual Thinking Machines”. This is the second book that presents the results of research in the area of thinking and understanding carried out by authors in the newly founded the Queen Jadwiga Research Institute of Understanding. In this book, the new term knowledge implementation is introduced to denote the new method of the meaningful learning in the context of machine understanding. SUS ability to understand is related to the different categories of objects such as the category of visual objects, the category of sensory objects and the category of text objects. In this book, new terms and concepts are introduced in order to describe and explain some issues connected with SUS development. These terms are explained by referring to the content of our books and other our works rather than to existing literature in related areas of research. This book raises many questions that are discussed in the area of cognitive science or philosophy of mind.
Book Synopsis Advances in Financial Machine Learning by : Marcos Lopez de Prado
Download or read book Advances in Financial Machine Learning written by Marcos Lopez de Prado and published by John Wiley & Sons. This book was released on 2018-01-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Book Synopsis Grokking Machine Learning by : Luis Serrano
Download or read book Grokking Machine Learning written by Luis Serrano and published by Simon and Schuster. This book was released on 2021-12-14 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. You'll also pick up practical skills for cleaning and preparing data.
Book Synopsis Semantic Agent Systems by : Atilla Elci
Download or read book Semantic Agent Systems written by Atilla Elci and published by Springer. This book was released on 2011-03-16 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semantic agent systems are about the integration of the semantic Web, software agents, and multi-agent systems technologies. Like in the past (e.g. biology and informatics yielding bioinformatics) a whole new perspective is emerging with semantic agent systems. In this context, the semantic Web is a Web of semantically linked data which aims to enable man and machine to execute tasks in tandem. Here, software agents in a multi-agent system as delegates of humans are endowed with power to use semantically linked data. This edited book “Semantic Agent Systems: Foundations and Applications” proposes contributions on a wide range of topics on foundations and applications written by a selection of international experts. It first introduces in an accessible style the nature of semantic agent systems. Then it explores with numerous illustrations new frontiers in software agent technology. “Semantic Agent Systems: Foundations and Applications” is recommended for scientists, experts, researchers, and learners in the field of artificial intelligence, the semantic Web, software agents, and multi-agent systems technologies.
Book Synopsis Machine Learning by : Ethem Alpaydin
Download or read book Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2016-10-07 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of “data science,” and discusses the ethical and legal implications for data privacy and security.
Book Synopsis The SAGE Handbook of Human–Machine Communication by : Andrea L. Guzman
Download or read book The SAGE Handbook of Human–Machine Communication written by Andrea L. Guzman and published by SAGE. This book was released on 2023-06-01 with total page 1019 pages. Available in PDF, EPUB and Kindle. Book excerpt: The SAGE Handbook of Human-Machine Communication has been designed to serve as the touchstone text for researchers and scholars engaging in new research in this fast-developing field. Chapters provide a comprehensive grounding of the history, methods, debates and theories that contribute to the study of human-machine communication. Further to this, the Handbook provides a point of departure for theorizing interactions between people and technologies that are functioning in the role of communicators, and for considering the theoretical and methodological implications of machines performing traditionally ‘human’ roles. This makes the Handbook the first of its kind, and a valuable resource for students and scholars across areas such as communication, media and information studies, and computer science, as well as for practitioners, engineers and researchers interested in the foundational elements of this emerging field. Part 1: Histories and Trajectories Part 2: Approaches and Methods Part 3: Concepts and Contexts Part 4: Technologies and Applications
Book Synopsis The Knowledge Machine: How Irrationality Created Modern Science by : Michael Strevens
Download or read book The Knowledge Machine: How Irrationality Created Modern Science written by Michael Strevens and published by Liveright Publishing. This book was released on 2020-10-13 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: “The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.
Book Synopsis A Human's Guide to Machine Intelligence by : Kartik Hosanagar
Download or read book A Human's Guide to Machine Intelligence written by Kartik Hosanagar and published by Penguin. This book was released on 2020-03-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.
Book Synopsis Machine Learning for Kids by : Dale Lane
Download or read book Machine Learning for Kids written by Dale Lane and published by No Starch Press. This book was released on 2021-01-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+
Download or read book Moral Machines written by Wendell Wallach and published by Oxford University Press. This book was released on 2010-07-15 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Moral Machines is a fine introduction to the emerging field of robot ethics. There is much here that will interest ethicists, philosophers, cognitive scientists, and roboticists." ---Peter Danielson, Notre Dame Philosophical Reviews --
Book Synopsis Understanding and Interpreting Machine Learning in Medical Image Computing Applications by : Danail Stoyanov
Download or read book Understanding and Interpreting Machine Learning in Medical Image Computing Applications written by Danail Stoyanov and published by Springer. This book was released on 2018-10-23 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.
Book Synopsis Summer of Simulation by : John Sokolowski
Download or read book Summer of Simulation written by John Sokolowski and published by Springer. This book was released on 2019-05-07 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on the “Summer Simulation Multi-Conference” (SCSC), which has been a prominent platform for the dissemination of scholarly research in the M&S community for the last 50 years. In keeping with the conference’s seasonal title, the authors have called this half-century “the summer of simulation,” and it has led not only to simulation-based disciplines but also simulation as a discipline. This book discusses contributions from the SCSC in four sections. The first section is an introduction to the work. The second section is devoted to contributions from simulation research fellows who were associated with the SCSC, while the third section features the SCSC’s most influential contributions. Lastly, the fourth section includes contributions from the best papers in the last five years. Features: • A comprehensive volume dedicated to one of the simulation domain’s major conferences: the SCSC • Offers a scientometric analysis of the SCSC • Revisits high-impact topics from 50 years of the SCSC • Includes chapters by simulation research fellows associated with the SCSC • Presents updated best-paper contributions from the recent conference This work will be of value to anyone interested in the evolution of modeling and simulation over the last fifty years. Readers will gain a perspective on what drove this evolution, and develop an understanding of the key contributions that allowed this technology to grow into its own academic discipline and profession.
