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Introduction to Deep Learning
A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basi...
Statistical Language Learning
This text introduces statistical language processing techniques--word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic word classes, word-sense disambiguation--along with the underlying mathematics and chapter exercises.
Introduction to Artificial Intelligence
Can computers think? Can they use reason to develop their own concepts, solve complex problems, understand our languages? This updated edition of a comprehensive survey includes extensive new text on "Artificial Intelligence in the 21st Century," introducing deep neural networks, conceptual graphs, languages of thought, mental models, metacognition, economic prospects, and research toward human-level AI. Ideal for both lay readers and students of computer science, the original text features abundant illustrations, diagrams, and photographs as well as challenging exercises. Lucid, easy-to-read discussions examine problem-solving methods and representations, game playing, automated understanding of natural languages, heuristic search theory, robot systems, heuristic scene analysis, predicate-calculus theorem proving, automatic programming, and many other topics.
Artificial Intelligence Programming
Artificial intelligence research has thrived in the years since this best-selling AI classic was first published. The revision encompasses these advances by adapting its coding to Common Lisp, the well-documented language standard, and by bringing together even more useful programming tools. Today's programmers in AI will find this volume's superior coverage of programming techniques and easily applicable style anything but common.
Foundations of Statistical Natural Language Processing
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing
This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.
The Oxford Handbook of the History of Linguistics
In this outstanding book leading scholars from around the world examine the history of linguistics from ancient origins to the present. They consider every aspect of the field from language origins to neurolinguistics, explore linguistic traditions in east and west, chronicle centuries of explanations for language structures, meanings, and usage, and look at how it has been practically applied. The book is organized in six parts. The first looks at the origins of language, the invention of writing, the nature of gesture, and sign languages. Part II examines the history of the analysis and description of sound systems. Part III considers the history of linguistics in China, Korea, Japan, Indi...
AI & I
A concise and illuminating history of the field of artificial intelligence from one of its earliest and most respected pioneers. AI & I is an intellectual history of the field of artificial intelligence from the perspective of one of its first practitioners, Eugene Charniak. Charniak entered the field in 1967, roughly 12 years after AI’s founding, and was involved in many of AI’s formative milestones. In this book, he traces the trajectory of breakthroughs and disappointments of the discipline up to the current day, clearly and engagingly demystifying this oft revered and misunderstood technology. His argument is controversial but well supported: that classical AI has been almost uniform...
The Form of Information in Science
DOES DISCOURSE HAVE A 'STRUCTURE'? HARRIS'S REVOLUTION IN LINGUISTICS As a freshman back in 1947 I discovered that within the various academic divisions and subdivisions of the University of Pennsylvania there existed a something (it was not a Department, but a piece of the Anthropology Department) called 'Linguistic Analysis'. I was an untalented but enthusiastic student of Greek and a slightly more talented student of German, as well as the son of a translator, so the idea of 'Linguistic Analysis' attracted me, sight unseen, and I signed up for a course. It turned out that 'Linguistic Analysis' was essentially a graduate program - I and another undergraduate called Noam Chomsky were the on...
