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.

Deep Learning

This paper proposes a paradigm for managing the dynamic aspects of organizational knowledge creating processes. Its central theme is that organizational knowledge is created through a continuous dialogue between tacit and explicit knowledge. The nature of this dialogue is examined and four patterns of interaction involving tacit and explicit knowledge are identified. It is argued that while new knowledge is developed by individuals, organizations play a critical role in articulating and amplifying that knowledge. A theoretical framework is developed which provides an analytical perspective on the constituent dimensions of knowledge creation. This framework is then applied in two operational models for facilitating the dynamic creation of appropriate organizational knowledge.

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A Dynamic Theory of Organizational Knowledge Creation

The concept of a linguistic variable and its application to approximate reasoning—II☆

A circumplex model of affect

The teaching of qualitative analysis in the social sciences is rarely undertaken in a structured way. This handbook is designed to remedy that and to present students and researchers with a systematic method for interpreting qualitative data', whether derived from interviews, field notes, or documentary materials. The special emphasis of the book is on how to develop theory through qualitative analysis. The reader is provided with the tools for doing qualitative analysis, such as codes, memos, memo sequences, theoretical sampling and comparative analysis, and diagrams, all of which are abundantly illustrated by actual examples drawn from the author's own varied qualitative research and research consultations, as well as from his research seminars. Many of the procedural discussions are concluded with rules of thumb that can usefully guide the researchers' analytic operations. The difficulties that beginners encounter when doing qualitative analysis and the kinds of persistent questions they raise are also discussed, as is the problem of how to integrate analyses. In addition, there is a chapter on the teaching of qualitative analysis and the giving of useful advice during research consultations, and there is a discussion of the preparation of material for publication. The book has been written not only for sociologists but for all researchers in the social sciences and in such fields as education, public health, nursing, and administration who employ qualitative methods in their work.

Qualitative analysis for social scientists

Ten years after writing the definitive, international bestselling book on political debate and messaging, George Lakoff returns with new strategies about how to frame today's essential issues. Called the "father of framing" by The New York Times, Lakoff explains how framing is about ideas-ideas that come before policy, ideas that make sense of facts, ideas that are proactive not reactive, positive not negative, ideas that need to be communicated out loud every day in public. The ALL NEW Don't Think of an Elephant! picks up where the original book left off-delving deeper into how framing works, how framing has evolved in the past decade, how to speak to people who harbor elements of both progressive and conservative worldviews, how to counter propaganda and slogans, and more. In this updated and expanded edition, Lakoff, urges progressives to go beyond the typical laundry list of facts, policies, and programs and present a clear moral vision to the country-one that is traditionally American and can become a guidepost for developing compassionate, effective policy that upholds citizens' well-being and freedom.

The ALL NEW Don't Think of an Elephant!: Know Your Values and Frame the Debate

• Para la m a y o r í a de la gente, la m e t á f o r a es un recurso de la i m a g i n a c i ó n poé t ica , y los ademanes r e tó r i cos , una c u e s t i ó n de lenguaje extraordinario m á s que ordinar io . E s m á s , la m e t á f o r a se contempla ca r ac t e r í s t i c amen te como u n rasgo só lo del lenguaje, cosa de palabras m á s que de pensamiento o acc ión . P o r esta r a z ó n , la mayor í a de la gente piensa que pueden a r r eg l á r selas perfectamente sin me tá fo ras . Nosot ros hemos llegado a la c o n c l u s i ó n de que la me tá fo ra , por el contrario, impregna la vida cotidiana, no solamente el lenguaje, sino t a m b i é n el pensamiento y la acc ión . Nuestro sistema conceptual ordinar io , en t é r m i n o s del cual pensamos y actuamos, es fundamentalmente de naturaleza metafór ica . L o s conceptos que rigen nuestro pensamiento no son s implemente asunto del intelecto. R i g en t a m b i é n nuestro funcionamiento cotidiano, hasta los detalles más mundanos. Nuestros conceptos estructuran lo que percibimos, c ó m o nos movemos en el mundo , la manera en que nos relacionamos con otras personas. A s í que nuestro sistema conceptual d e s e m p e ñ a un papel central en la def in ic ión de nuestras realidades cotidianas. Si estamos en lo cierto al sugerir que nuestro sistema conceptual es en gran medida me ta fó r i co , la manera en que pensamos, lo que experimentamos y lo que hacemos cada día también es en gran medida cosa de m e t á f o r a s .

Metáforas de la vida cotidiana

Foreword by Howard Dean Introduction by Don Hazen Preface: Reframing Is Social Change Part I: Theory and Application Framing 101: How to Take Back Public Discourse Enter the Terminator! Whatis in a Word? Plenty, if Itis Marriage Metaphors of Terror Metaphors That Kill Betrayal of Trust: Beyond Lying Part II: From Theory to Action What the Right Wants What Unites Progressives FAQ How to Respond to Conservatives

Don't Think of an Elephant!: Know Your Values and Frame the Debate--The Essential Guide for Progressives

The Cognitive Model of Anger Inherent in American English By George Lakoﬂ&#39; and Zolten Kovecses Linguistics Department University of California at Berkeley May, 1983

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The cognitive model of anger inherent in American English

Evidence is presented to show that the role of a generative grammar of a natural language is not merely to generate the grammatical sentences of that language, but also to relate them to their logical forms. The notion of logical form is to be made sense of in terms a ‘natural logic’, a logical for natural language, whose goals are to express all concepts capable of being expressed in natural language, to characterize all the valid inferences that can be made in natural language, and to mesh with adequate linguistic descriptions of all natural languages. The latter requirement imposes empirical linguistic constraints on natural logic. A number of examples are discussed.

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George Lakoff

Papers

The ALL NEW Don't Think of an Elephant!: Know Your Values and Frame the Debate

Metáforas de la vida cotidiana

Don't Think of an Elephant!: Know Your Values and Frame the Debate--The Essential Guide for Progressives

The cognitive model of anger inherent in American English

Linguistics and Natural Logic