Download or read book Language Machines written by Jeffrey Masten and published by Psychology Press. This book was released on 1997 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1998. Routledge is an imprint of Taylor & Francis, an informa company.
Download or read book Language Machines written by Jeffrey Masten and published by Routledge. This book was released on 2016-03-23 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Language Machines questions any easily progressive model of technological change, demonstrating the persistence rather than the obsolescence of language technologies over time, the continuous and complicated overlap of pens, presses, screens and voice. In these essays new technologies do not simply replace, but rather draw upon, absorb, displace and resituate earlier technologies.
Download or read book Languages and Machines written by Thomas A. Sudkamp and published by Pearson Education India. This book was released on 2008 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Language of Machines written by Robert W. Floyd and published by W H Freeman & Company. This book was released on 1994 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, authoritative text for courses in theory of computability and languages. The authors redefine the building blocks of automata theory by offering a single unified model encompassing all traditional types of computing machines and real world electronic computers. This reformulation of computablity and formal language theory provides a framework for building a body of knowledge. A solutions manual and an instructor's software disk are also available.
Download or read book A Concise Introduction to Languages and Machines written by Alan P. Parkes and published by Springer Science & Business Media. This book was released on 2009-06-29 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Concise Introduction to Languages, Machines and Logic provides an accessible introduction to three key topics within computer science: formal languages, abstract machines and formal logic. Written in an easy-to-read, informal style, this textbook assumes only a basic knowledge of programming on the part of the reader. The approach is deliberately non-mathematical, and features: - Clear explanations of formal notation and jargon, - Extensive use of examples to illustrate algorithms and proofs, - Pictorial representations of key concepts, - Chapter opening overviews providing an introduction and guidance to each topic, - End-of-chapter exercises and solutions, - Offers an intuitive approach to the topics. This reader-friendly textbook has been written with undergraduates in mind and will be suitable for use on course covering formal languages, formal logic, computability and automata theory. It will also make an excellent supplementary text for courses on algorithm complexity and compilers.
Download or read book Machines Languages and Computation written by Peter J. Denning and published by Prentice Hall. This book was released on 1978 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Languages Machines and Logic written by Alan P. Parkes and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A well-written and accessible introduction to the most important features of formal languages and automata theory. It focuses on the key concepts, illustrating potentially intimidating material through diagrams and pictorial representations, and this edition includes new and expanded coverage of topics such as: reduction and simplification of material on Turing machines; complexity and O notation; propositional logic and first order predicate logic. Aimed primarily at computer scientists rather than mathematicians, algorithms and proofs are presented informally through examples, and there are numerous exercises (many with solutions) and an extensive glossary.
Download or read book The Apprentice written by Pilar Molina Llorente and published by Perfection Learning. This book was released on 1994-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Working as an artist's apprentice in Renaissance Florence, thirteen-year-old Arduino makes a discovery which may cost him the chance to become a painter.
Download or read book Where Humans Meet Machines written by Amy Neustein and published by Springer Science & Business Media. This book was released on 2013-06-22 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Editors Amy Neustein and Judith A. Markowitz have recruited a talented group of contributors to introduce the next generation of natural language technologies to resolve some of the most vexing natural-language problems that compromise the performance of speech systems today. This fourteen-chapter anthology consists of contributions from industry scientists and from academicians working at major universities in North America and Europe. They include researchers who have played a central role in DARPA-funded programs and developers who craft real-world solutions for corporations. This anthology is aimed at speech engineers, system developers, computer scientists, AI researchers, and others interested in utilizing natural-language technology in both spoken and text-based applications.
Download or read book Scripts Grooves and Writing Machines written by Lisa Gitelman and published by Stanford University Press. This book was released on 1999 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The phonograph and the typewriter may be things of the past, but this book will resonate with readers who are engaged daily with computer networks, hypertexts, and the forms that mass media will take in the new century."--BOOK JACKET.
Download or read book Knowledge Machines written by Denise E. Murray and published by Routledge. This book was released on 2014-06-11 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a wide-ranging survey of the sociolinguistic issues raised by the impact of information technology. The author demonstrates how and in which ways the new technologies both affect human communication and are in turn affected by the way people communicate using the technologies.
Download or read book Natural Language Processing with TensorFlow written by Thushan Ganegedara and published by Packt Publishing Ltd. This book was released on 2018-05-31 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful.
Download or read book Mentality and Machines written by Keith Gunderson and published by U of Minnesota Press. This book was released on 1985 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mentality and Machines was first published in 1985. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions. Mentality and Machines — with a new preface and an extended postscript—is a general essay on the philosophy of mind, oriented to philosophical and psychological questions about real as well as imagined, robots and machines. The second edition retains all of the essays from the original book, including Gunderson's influential critique ("The Imitation Game") of A.M. Turing's treatment of the question "Can machines think?" and his controversial distinction between program-receptive and program-resistant aspects of the mind. This edition's postscript includes further reflections on these themes and others, and relates them to recent writings of other philosophers and computer scientists.
Download or read book Human and Machines written by Jun Gu and published by Springer Nature. This book was released on 2022-10-13 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shares Chinese scholars’ philosophical views on artificial intelligence. The discussions range from the foundations of AI—the Turing test and creation of machine intelligence—to recent applications of AI, including decisions in games, natural languages, pattern recognition, prediction in economic contexts, autonomous behaviors, and collaborative intelligence, with the examples of AlphaGo, Microsoft’s Xiao Bing, medical robots, etc. The book’s closing chapter focuses on Chinese machines and explores questions on the cultural background of artificial intelligence. Given its scope, the book offers a valuable resource for all members of the general public who are interested in the future development of artificial intelligence, especially from the perspective of respected Chinese scholars.
Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production
Download or read book Introduction to Natural Language Processing written by Jacob Eisenstein and published by MIT Press. This book was released on 2019-10-01 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
Download or read book Linguistics for the Age of AI written by Marjorie Mcshane and published by MIT Press. This book was released on 2021-03-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.
