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A landmark volume that explores the interconnected nature of technologies and rhetorical practice
Rhetorical Machines addresses new approaches to studying computational processes within the growing field of digital rhetoric. While computational code is often seen as value-neutral and mechanical, this volume explores the underlying, and often unexamined, modes of persuasion this code engages. In so doing, it argues that computation is in fact rife with the values of those who create it and thus has powerful ethical and moral implications. From Socrates's critique of writing in Plato's Phaedrus to emerging new media and internet culture, the scholars assembled here provide insight into how computation and rhetoric work together to produce social and cultural effects. This multidisciplinary volume features contributions from scholar-practitioners acrossA landmark volume that explores the interconnected nature of technologies and rhetorical practice Rhetorical Machines addresses new approaches to studying computational processes within the growing field of digital rhetoric. While computational code is often seen as value-neutral and mechanical,
A landmark volume that explores the interconnected nature of technologies and rhetorical practice Rhetorical Machines addresses new approaches to studying computational processes within the growing field of digital rhetoric. While computational code is often seen as value-neutral and mechanical,
Encompasses the full range of computational science and engineering from modelling to solution, both analytical and numerical. It develops a framework for the equations and numerical methods of applied mathematics. Gilbert Strang has taught this material to thousands of engineers and scientists
Detailed and pedagogical account of computational statistical physics, this book covers both theoretical foundations of equilibrium and non-equilibrium statistical physics, and also modern, computational applications. The accessible and self-contained approach adopted by the authors makes this book
Covers basic mathematical, statistical and programming problems in computational statisticsAddresses both univariate and multivariate statistical data analysis and applications in finance, the life sciences and other disciplines Features R sniplets in the text and computer programs on GitHub that
An essential guide for teaching and learning computational art and design: exercises, assignments, anecdotes, and interviews; more than 150 color images. This book is an essential resource for art educators and artists who want to explore code as a creative medium, and a guide for computer
Through examples and analogies, Computational Thinking for the Modern Problem Solver introduces computational thinking as part of an introductory computing course and shows how computer science concepts are applicable to other fields. It keeps the material accessible and relevant to noncomputer
In Cloud Ethics Louise Amoore examines how machine learning algorithms are transforming the ethics and politics of contemporary society. Conceptualizing algorithms as ethicopolitical entities that are entangled with the data attributes of people, Amoore outlines how algorithms give incomplete
This book reexamines reflection and ethics for teachers, and argues the case for ensuring teaching practices are educational and professional rather than simply technical or clinical. Demonstrating that theory is indispensable when it comes to professional deliberation and educational practice, the
This book covers topics that are at the intersection of business ethics and governance as they pertain to entrepreneurship and finance. It is the first focused work that links entrepreneurship and finance to governance and business ethics, rather than explore them separately. The chapters highlight
Autonomous AI systems need complex computational techniques for planning and performing actions. Planning and acting require significant deliberation because an intelligent system must coordinate and integrate these activities in order to act effectively in the real world. This book presents a
An introduction to computational complexity theory, its connections and interactions with mathematics, and its central role in the natural and social sciences, technology, and philosophyMathematics and Computation provides a broad, conceptual overview of computational complexity theory--the
Wolfgang Ernst's new work, Technol gos in Being, in its explicit media-scientific approach, aligns with the politics of the thinking media series to publish innovative works that advance media studies towards the 'new sciences.' Ernst's invites readers to re-adjust their ideas of Media Studies: the
This beginning graduate textbook describes both recent achievements and classical results of computational complexity theory. Requiring essentially no background apart from mathematical maturity, the book can be used as a reference for self-study for anyone interested in complexity, including
The first introductory textbook in the emerging, fast-developing field of computational psychiatry.Computational psychiatry applies computational modeling and theoretical approaches to psychiatric questions, focusing on building mathematical models of neural or cognitive phenomena relevant to
How do infants learn a language? Why and how do languages evolve? How do we understand a sentence? This book explores these questions using recent computational models that shed new light on issues related to language and cognition. The chapters in this collection propose original analyses of
A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques.This textbook provides a technical perspective on natural language processing--methods
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine
Part I Transparency in Machine Learning.- Part II Visual Explanation of Machine Learning Process.- Part III Algorithmic Explanation of Machine Learning Models.- Part IV User Cognitive Responses in ML-Based Decision Making.- Part V Human and Evaluation of Machine Learning.- Part VI Domain Knowledge
The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer. In this richly illustrated book, Shannon's mathematical theory of information is used to explore the metabolic efficiency of neurons,