Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Linguistics for the Age of AI
🌠 Top Free Web Programming Books - 100% Free or Open Source!
  • Title Linguistics for the Age of AI
  • Author(s) Marjorie McShane, Sergei Nirenburg
  • Publisher: The MIT Press (March 2, 2021); eBook (MIT Open Access Edition)
  • License(s): CC BY-NC-ND 4.0
  • Hardcover 448 pages
  • eBook PDF files
  • Language: English
  • ISBN-10: 0262045583
  • ISBN-13: 978-0262045582
  • Share This:  
`

Book Description

This book provides 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.

This book summarizes an exciting approach to knowledge-rich natural language understanding, in the context of language - using AI agents. Anyone interested in building cognitive systems that use language should read this book.

About the Authors
  • Marjorie McShane and Sergei Nirenburg are on the faculty of the Cognitive Science Department at Rensselaer Polytechnic Institute.
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Foundation Models for Natural Language Processing

    This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts.

  • Speech and Language Processing (Dan Jurafsky, et al)

    This text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. It describes a unified vision of speech and language processing. Emphasis is on practical and scientific applications.

  • Computational Linguistics: Models, Resources, Applications

    This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP). It will be of interest and practical use to a wide range of linguists.

  • O'Reilly® Natural Language Processing with Python

    This book offers a highly accessible introduction to natural language processing (NLP), the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.

  • Hands-On Natural Language Processing with Python

    It teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today's NLP challenges. you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges.

  • Natural Language Processing Succinctly (Joseph Booth)

    This book will guide readers through designing a simple system that can interpret and provide reasonable responses to written English text. With this foundation, readers will be prepared to tackle the greater challenges of natural language development.

  • NLP - Skills for Learning (Peter Freeth)

    This is a book about the application of NLP (Neuro Linguistic Programming) in teaching, training and education. It is a book about NLP for trainers and a general introduction to NLP - all in one.

  • Natural Language Processing for the Working Programmer

    This book is a guide to the wonderful world of language processing for the practical working programmer, using Haskell. It is about that type of information - techniques that so-called computational linguists use to analyze the structure of human language.

  • Natural Language Processing for Prolog Programmers

    An examination of natural language processing in Prolog for those who know Prolog but not linguistics, this book enables students to move quickly into writing and working in useful software for natural language processing (NLP).

  • Prolog and Natural-Language Analysis (Fernando Pereira, et al)

    A concise and practical introduction to logic programming and the language Prolog both as vehicles for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing (NLP) systems.

  • Natural Language Processing Techniques in Prolog

    This book introduces the subject through the discussion and development of various computer programs which illustrate some of the basic concepts and techniques of natural language processing (NLP).

  • Analyzing Linguistic Data: Introduction to Statistics using R

    A straightforward introduction to the statistical analysis of language, designed for those with a non-mathematical background. Using the leading statistics programme 'R'. Suitable for all those working with quantitative language data.

  • How Language Works: The Cognitive Science of Linguistics

    This book offers general readers a personal tour of the intricate workings of language. It will focus on a narrow range of topics and themes; there will be no pretense of covering the field in anything like a complete fashion.

  • Essentials of Linguistics (Catherine Anderson)

    This book is about the core areas of theoretical linguistics (phonetics, phonology, morphology, syntax, and semantics), supplemented with discussion of psycholinguistic and neurolinguistic findings. It is suitable for any beginning learner of linguistics.

  • Syntactic Theory: A Formal Introduction (Ivan A. Sag, et al)

    This is a textbook that makes it truly fun to teach introductory syntax. It is thoroghly data-driven and teaches the student to pay attention to empirical details and to find linguistic patterns and explanations for them.

Book Categories
:
Other Categories
Resources and Links