Download or read book Machine Learning in Action written by Peter Harrington and published by Simon and Schuster. This book was released on 2012-04-03 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predicting numeric values: regression Tree-based regression PART 3 UNSUPERVISED LEARNING Grouping unlabeled items using k-means clustering Association analysis with the Apriori algorithm Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS Using principal component analysis to simplify data Simplifying data with the singular value decomposition Big data and MapReduce

Download or read book Knowledge in Action written by Raymond Reiter and published by MIT Press. This book was released on 2001-07-27 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specifying and implementing dynamical systems with the situation calculus. Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community. This book presents a comprehensive treatment of these ideas, basing its theoretical and implementation foundations on the situation calculus, a dialect of first-order logic. Within this framework, it develops many features of dynamical systems modeling, including time, processes, concurrency, exogenous events, reactivity, sensing and knowledge, probabilistic uncertainty, and decision theory. It also describes and implements a new family of high-level programming languages suitable for writing control programs for dynamical systems. Finally, it includes situation calculus specifications for a wide range of examples drawn from cognitive robotics, planning, simulation, databases, and decision theory, together with all the implementation code for these examples. This code is available on the book's Web site.

Download or read book Artificial Intelligence in Action written by Charles Platt and published by Trillium Press. This book was released on 1985-05-01 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence written by John Haugeland and published by MIT Press. This book was released on 1989-01-06 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Machines who think—how utterly preposterous," huff beleaguered humanists, defending their dwindling turf. "Artificial Intelligence—it's here and about to surpass our own," crow techno-visionaries, proclaiming dominion. It's so simple and obvious, each side maintains, only a fanatic could disagree. Deciding where the truth lies between these two extremes is the main purpose of John Haugeland's marvelously lucid and witty book on what artificial intelligence is all about. Although presented entirely in non-technical terms, it neither oversimplifies the science nor evades the fundamental philosophical issues. Far from ducking the really hard questions, it takes them on, one by one. Artificial intelligence, Haugeland notes, is based on a very good idea, which might well be right, and just as well might not. That idea, the idea that human thinking and machine computing are "radically the same," provides the central theme for his illuminating and provocative book about this exciting new field. After a brief but revealing digression in intellectual history, Haugeland systematically tackles such basic questions as: What is a computer really? How can a physical object "mean" anything? What are the options for computational organization? and What structures have been proposed and tried as actual scientific models for intelligence? In a concluding chapter he takes up several outstanding problems and puzzles—including intelligence in action, imagery, feelings and personality—and their enigmatic prospects for solution.

Download or read book Readings in Artificial Intelligence written by Bonnie Lynn Webber and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readings in Artificial Intelligence focuses on the principles, methodologies, advancements, and approaches involved in artificial intelligence. The selection first elaborates on representations of problems of reasoning about actions, a problem similarity approach to devising heuristics, and optimal search strategies for speech understanding control. Discussions focus on comparison with existing speech understanding systems, empirical comparisons of the different strategies, analysis of distance function approximation, problem similarity, problems of reasoning about action, search for solution in the reduction system, and relationship between the initial search space and the higher level search space. The book then examines consistency in networks of relations, non-resolution theorem proving, using rewriting rules for connection graphs to prove theorems, and closed world data bases. The manuscript tackles a truth maintenance system, elements of a plan-based theory of speech acts, and reasoning about knowledge and action. Topics include problems in reasoning about knowledge, integration knowledge and action, models of plans, compositional adequacy, truth maintenance mechanisms, dialectical arguments, and assumptions and the problem of control. The selection is a valuable reference for researchers wanting to explore the field of artificial intelligence.

Download or read book The Executive Guide to Artificial Intelligence written by Andrew Burgess and published by Springer. This book was released on 2017-11-15 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.

Download or read book Action Programming Languages written by Michael Thielscher and published by Morgan & Claypool Publishers. This book was released on 2008 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence. Action Programming is the art and science of devising high-level control strategies for autonomous systems which employ a mental model of their environment and which reason about their actions as a means to achieve their goals. Applications of this programming paradigm include autonomous software agents, mobile robots with high-level reasoning capabilities, and General Game Playing. These lecture notes give an in-depth introduction to the current state-of-the-art in action programming. The main topics are knowledge representation for actions, procedural action programming, planning, agent logic programs, and reactive, behavior-based agents. The only prerequisite for understanding the material in these lecture notes is some general programming experience and basic knowledge of classical first-order logic.

Download or read book Social Action and Artificial Intelligence written by G. Nigel Gilbert and published by . This book was released on 1986 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Promise of Artificial Intelligence written by Brian Cantwell Smith and published by MIT Press. This book was released on 2019-10-08 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: An argument that—despite dramatic advances in the field—artificial intelligence is nowhere near developing systems that are genuinely intelligent. In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability “reckoning,” and argues that it does not lead to full human judgment—dispassionate, deliberative thought grounded in ethical commitment and responsible action. Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins (“good old-fashioned AI,” or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself—what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.

Download or read book Artificial Intelligence written by Jerry Kaplan and published by Oxford University Press. This book was released on 2016-09-01 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you.

Download or read book Artificial Intelligence written by Melanie Mitchell and published by Farrar, Straus and Giroux. This book was released on 2019-10-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

Download or read book Artificial Intelligence for a Better Future written by Bernd Carsten Stahl and published by Springer Nature. This book was released on 2021-03-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book proposes a novel approach to Artificial Intelligence (AI) ethics. AI offers many advantages: better and faster medical diagnoses, improved business processes and efficiency, and the automation of boring work. But undesirable and ethically problematic consequences are possible too: biases and discrimination, breaches of privacy and security, and societal distortions such as unemployment, economic exploitation and weakened democratic processes. There is even a prospect, ultimately, of super-intelligent machines replacing humans. The key question, then, is: how can we benefit from AI while addressing its ethical problems? This book presents an innovative answer to the question by presenting a different perspective on AI and its ethical consequences. Instead of looking at individual AI techniques, applications or ethical issues, we can understand AI as a system of ecosystems, consisting of numerous interdependent technologies, applications and stakeholders. Developing this idea, the book explores how AI ecosystems can be shaped to foster human flourishing. Drawing on rich empirical insights and detailed conceptual analysis, it suggests practical measures to ensure that AI is used to make the world a better place.

Download or read book Transhumanism The Proper Guide to a Posthuman Condition or a Dangerous Idea written by Wolfgang Hofkirchner and published by Springer Nature. This book was released on 2020-12-12 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the contributions of the transhumanism approach to technology, in particular the contributed chapters are wary of the implications of this popular idea. The volume is organized into four parts concerning philosophical, military, technological and sociological aspects of transhumanism, but the reader is free to choose various reading patterns. Topics discussed include gene editing, the singularity, ethical machines, metaphors in AI, mind uploading, and the philosophy of art, and some perspectives taken or discussed examine transhumanism within the context of the philosophy of technology, transhumanism as a derailed anthropology, and critical sociological aspects that consider transhumanism in the context of topical concerns such as whiteness, maleness, and masculinity. The book will be of value to researchers engaged with artificial intelligence, and the ethical, societal, and philosophical impacts of science and technology.

Download or read book Proceedings written by American Association for Artificial Intelligence and published by . This book was released on 2004 with total page 1084 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings from the latest meeting of the leading AI conference; includes theoretical, experimental, and empirical work. The National Conference on Artificial Intelligence remains the bellwether for research in artificial intelligence. Leading AI researchers and practitioners as well as scientists and engineers in related fields present theoretical, experimental, and empirical results, covering a broad range of topics that include principles of cognition, perception, and action; the design, application, and evaluation of AI algorithms and systems; architectures and frameworks for classes of AI systems; and analyses of tasks and domains in which intelligent systems perform. The Innovative Applications of Artificial Intelligence conference highlights successful applications of AI technology; explores issues, methods, and lessons learned in the development and deployment of AI applications; and promotes an interchange of ideas between basic and applied AI. This volume presents the proceedings of the latest conferences, held in July, 2004.

Download or read book The AI Marketing Canvas written by Raj Venkatesan and published by Stanford University Press. This book was released on 2021-05-18 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a direct, actionable plan CMOs can use to map out initiatives that are properly sequenced and designed for success—regardless of where their marketing organization is in the process. The authors pose the following critical questions to marketers: (1) How should modern marketers be thinking about artificial intelligence and machine learning? and (2) How should marketers be developing a strategy and plan to implement AI into their marketing toolkit? The opening chapters provide marketing leaders with an overview of what exactly AI is and how is it different than traditional computer science approaches. Venkatesan and Lecinski, then, propose a best-practice, five-stage framework for implementing what they term the "AI Marketing Canvas." Their approach is based on research and interviews they conducted with leading marketers, and offers many tangible examples of what brands are doing at each stage of the AI Marketing Canvas. By way of guidance, Venkatesan and Lecinski provide examples of brands—including Google, Lyft, Ancestry.com, and Coca-Cola—that have successfully woven AI into their marketing strategies. The book concludes with a discussion of important implications for marketing leaders—for your team and culture.

Download or read book Deep Reinforcement Learning in Action written by Alexander Zai and published by Manning Publications. This book was released on 2020-04-28 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. About the book Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you’ll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and playing video games. Along the way, you’ll work with core algorithms, including deep Q-networks and policy gradients, along with industry-standard tools like PyTorch and OpenAI Gym. What's inside Building and training DRL networks The most popular DRL algorithms for learning and problem solving Evolutionary algorithms for curiosity and multi-agent learning All examples available as Jupyter Notebooks About the reader For readers with intermediate skills in Python and deep learning. About the author Alexander Zai is a machine learning engineer at Amazon AI. Brandon Brown is a machine learning and data analysis blogger. Table of Contents PART 1 - FOUNDATIONS 1. What is reinforcement learning? 2. Modeling reinforcement learning problems: Markov decision processes 3. Predicting the best states and actions: Deep Q-networks 4. Learning to pick the best policy: Policy gradient methods 5. Tackling more complex problems with actor-critic methods PART 2 - ABOVE AND BEYOND 6. Alternative optimization methods: Evolutionary algorithms 7. Distributional DQN: Getting the full story 8.Curiosity-driven exploration 9. Multi-agent reinforcement learning 10. Interpretable reinforcement learning: Attention and relational models 11. In conclusion: A review and roadmap

Download or read book Cambrian Intelligence written by Rodney Allen Brooks and published by MIT Press. This book was released on 1999 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Until the mid-1980s, AI researchers assumed that an intelligent system doing high-level reasoning was necessary for the coupling of perception and action. In this traditional model, cognition mediates between perception and plans of action. Realizing that this core AI, as it was known, was illusory, Rodney A. Brooks turned the field of AI on its head by introducing the behavior-based approach to robotics. The cornerstone of behavior-based robotics is the realization that the coupling of perception and action gives rise to all the power of intelligence and that cognition is only in the eye of an observer. Behavior-based robotics has been the basis of successful applications in entertainment, service industries, agriculture, mining, and the home. It has given rise to both autonomous mobile robots and more recent humanoid robots such as Brooks' Cog. This book represents Brooks' initial formulation of and contributions to the development of the behavior-based approach to robotics. It presents all of the key philosophical and technical ideas that put this "bottom-up" approach at the forefront of current research in not only AI but all of cognitive science.