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Author: L. Jean Camp
Publisher: MIT Press
ISBN: 9780262531979
Category : Business & Economics
Languages : en
Pages : 298
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Book Description
This book provides information on trust and risk to businesses that are developing electronic commerce systems and helps consumers understand the risks in using the Internet for purchases and show them how to protect themselves.
Author: Chris Kempes
Publisher: Seminar
ISBN: 9781947864184
Category : Science
Languages : en
Pages : 500
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Book Description
Why do computers use so much energy? What are the fundamental physical laws governing the relationship between the precise computation run by a system, whether artificial or natural, and how much energy that computation requires? This volume integrates concepts from diverse fields, cultivating a modern, nonequilibrium thermodynamics of computation.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309047404
Category : Computers
Languages : en
Pages : 287
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Book Description
Computers are increasingly the enabling devices of the information revolution, and computing is becoming ubiquitous in every corner of society, from manufacturing to telecommunications to pharmaceuticals to entertainment. Even more importantly, the face of computing is changing rapidly, as even traditional rivals such as IBM and Apple Computer begin to cooperate and new modes of computing are developed. Computing the Future presents a timely assessment of academic computer science and engineering (CS&E), examining what should be done to ensure continuing progress in making discoveries that will carry computing into the twenty-first century. Most importantly, it advocates a broader research and educational agenda that builds on the field's impressive accomplishments. The volume outlines a framework of priorities for CS&E, along with detailed recommendations for education, funding, and leadership. A core research agenda is outlined for these areas: processors and multiple-processor systems, data communications and networking, software engineering, information storage and retrieval, reliability, and user interfaces. This highly readable volume examines: Computer science and engineering as a discipline-how computer scientists and engineers are pushing back the frontiers of their field. How CS&E must change to meet the challenges of the future. The influence of strategic investment by federal agencies in CS&E research. Recent structural changes that affect the interaction of academic CS&E and the business environment. Specific examples of interdisciplinary and applications research in four areas: earth sciences and the environment, computational biology, commercial computing, and the long-term goal of a national electronic library. The volume provides a detailed look at undergraduate CS&E education, highlighting the limitations of four-year programs, and discusses the emerging importance of a master's degree in CS&E and the prospects for broadening the scope of the Ph.D. It also includes a brief look at continuing education.
Author: L. Jean Camp
Publisher: MIT Press
ISBN: 9780262531979
Category : Business & Economics
Languages : en
Pages : 298
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Book Description
This book provides information on trust and risk to businesses that are developing electronic commerce systems and helps consumers understand the risks in using the Internet for purchases and show them how to protect themselves.
Author: L. Jean Camp
Publisher: Springer Science & Business Media
ISBN: 1402080905
Category : Computers
Languages : en
Pages : 300
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Book Description
Designed for managers struggling to understand the risks in organizations dependent on secure networks, this book applies economics not to generate breakthroughs in theoretical economics, but rather breakthroughs in understanding the problems of security.
Author: Nathan L. Ensmenger
Publisher: MIT Press
ISBN: 0262302829
Category : Computers
Languages : en
Pages : 331
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Book Description
The contentious history of the computer programmers who developed the software that made the computer revolution possible. This is a book about the computer revolution of the mid-twentieth century and the people who made it possible. Unlike most histories of computing, it is not a book about machines, inventors, or entrepreneurs. Instead, it tells the story of the vast but largely anonymous legions of computer specialists—programmers, systems analysts, and other software developers—who transformed the electronic computer from a scientific curiosity into the defining technology of the modern era. As the systems that they built became increasingly powerful and ubiquitous, these specialists became the focus of a series of critiques of the social and organizational impact of electronic computing. To many of their contemporaries, it seemed the “computer boys” were taking over, not just in the corporate setting, but also in government, politics, and society in general. In The Computer Boys Take Over, Nathan Ensmenger traces the rise to power of the computer expert in modern American society. His rich and nuanced portrayal of the men and women (a surprising number of the “computer boys” were, in fact, female) who built their careers around the novel technology of electronic computing explores issues of power, identity, and expertise that have only become more significant in our increasingly computerized society. In his recasting of the drama of the computer revolution through the eyes of its principle revolutionaries, Ensmenger reminds us that the computerization of modern society was not an inevitable process driven by impersonal technological or economic imperatives, but was rather a creative, contentious, and above all, fundamentally human development.
Author: Adrian Mackenzie
Publisher: MIT Press
ISBN: 0262036827
Category : Social Science
Languages : en
Pages : 269
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Book Description
If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking. Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures. Mackenzie's account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.
Author: Robert Plant
Publisher: Cambridge University Press
ISBN: 1139463934
Category : Technology & Engineering
Languages : en
Pages : 363
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Book Description
Assessing the most valuable technology for an organization is becoming a growing challenge for business professionals confronted with an expanding array of options. This 2007 book is an A-Z compendium of technological terms written for the non-technical executive, allowing quick identification of what the term is and why it is significant. This is more than a dictionary - it is a concise review of the most important aspects of information technology from a business perspective: the major advantages, disadvantages and business value propositions of each term are discussed, as well as sources for further reading, and cross-referencing with other terms where applicable. The essential elements of each concept are covered in a succinct manner so the reader can quickly obtain the required knowledge without wading through exhaustive descriptions. With over 200 terms, this is a valuable reference for non- and semi-technical managers, executives and graduate students in business and technology management.
Author: Vojislav Kecman
Publisher: MIT Press
ISBN: 9780262112550
Category : Computers
Languages : en
Pages : 556
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Book Description
This textbook provides a thorough introduction to the field of learning from experimental data and soft computing. Support vector machines (SVM) and neural networks (NN) are the mathematical structures, or models, that underlie learning, while fuzzy logic systems (FLS) enable us to embed structured human knowledge into workable algorithms. The book assumes that it is not only useful, but necessary, to treat SVM, NN, and FLS as parts of a connected whole. Throughout, the theory and algorithms are illustrated by practical examples, as well as by problem sets and simulated experiments. This approach enables the reader to develop SVM, NN, and FLS in addition to understanding them. The book also presents three case studies: on NN-based control, financial time series analysis, and computer graphics. A solutions manual and all of the MATLAB programs needed for the simulated experiments are available.
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Author: Edmund Callis Berkeley
Publisher: Good Press
ISBN:
Category : Fiction
Languages : en
Pages : 248
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Book Description
"Giant brains; or, Machines that think" by Edmund Callis Berkeley. Published by Good Press. Good Press publishes a wide range of titles that encompasses every genre. From well-known classics & literary fiction and non-fiction to forgotten−or yet undiscovered gems−of world literature, we issue the books that need to be read. Each Good Press edition has been meticulously edited and formatted to boost readability for all e-readers and devices. Our goal is to produce eBooks that are user-friendly and accessible to everyone in a high-quality digital format.
