Artificial Intelligence And Natural Language
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Natural Language Processing In Artificial Intelligence
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Author : Brojo Kishore Mishra
language : en
Publisher: Apple Academic Press
Release Date : 2022-06
Natural Language Processing In Artificial Intelligence written by Brojo Kishore Mishra and has been published by Apple Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06 with categories.
Natural Language Processing in Artificial Intelligence, focuses on natural language processing, artificial intelligence, and allied areas. The book delves into natural language processing, which enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world.
Applied Natural Language Processing With Python
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Author : Taweh Beysolow II
language : en
Publisher: Apress
Release Date : 2018-09-12
Applied Natural Language Processing With Python written by Taweh Beysolow II and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-12 with Computers categories.
Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment. What You Will Learn Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim Manipulate and preprocess raw text data in formats such as .txt and .pdf Strengthen your skills in data science by learning both the theory and the application of various algorithms Who This Book Is For You should be at least a beginner in ML to get the most out of this text, but you needn’t feel that you need be an expert to understand the content.
Natural Language Processing
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Author : Yue Zhang
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-07
Natural Language Processing written by Yue Zhang and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-07 with Computers categories.
This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.
Artificial Intelligence Expert Systems Computer Vision And Natural Language Processing
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Author : William B. Gevarter
language : en
Publisher: William Andrew
Release Date : 1984
Artificial Intelligence Expert Systems Computer Vision And Natural Language Processing written by William B. Gevarter and has been published by William Andrew this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Computers categories.
The Natural Language For Artificial Intelligence
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Author : Dioneia Motta Monte-Serrat
language : en
Publisher: Elsevier
Release Date : 2021-04-06
The Natural Language For Artificial Intelligence written by Dioneia Motta Monte-Serrat and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-06 with Computers categories.
The Natural Language for Artificial Intelligence presents natural language as the next frontier because it identifies something that is most sought after by scholars: The universal structure of language that gives rise to the respective universal algorithm. In short, this book presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind that, at the same time, interprets the context of reality. It is a non-static approach to natural language, which is defined as a complex system whose parts interact with the ability to generate a new quality of behavior and whose dynamic elements are mapped in order to be understood and executed by intelligent systems, guiding the paradigms of cognitive computing. The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language, leading to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed, to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI. Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine.
Neural Representations Of Natural Language
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Author : Lyndon White
language : en
Publisher: Springer
Release Date : 2018-08-29
Neural Representations Of Natural Language written by Lyndon White and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-29 with Technology & Engineering categories.
This book offers an introduction to modern natural language processing using machine learning, focusing on how neural networks create a machine interpretable representation of the meaning of natural language. Language is crucially linked to ideas – as Webster’s 1923 “English Composition and Literature” puts it: “A sentence is a group of words expressing a complete thought”. Thus the representation of sentences and the words that make them up is vital in advancing artificial intelligence and other “smart” systems currently being developed. Providing an overview of the research in the area, from Bengio et al.’s seminal work on a “Neural Probabilistic Language Model” in 2003, to the latest techniques, this book enables readers to gain an understanding of how the techniques are related and what is best for their purposes. As well as a introduction to neural networks in general and recurrent neural networks in particular, this book details the methods used for representing words, senses of words, and larger structures such as sentences or documents. The book highlights practical implementations and discusses many aspects that are often overlooked or misunderstood. The book includes thorough instruction on challenging areas such as hierarchical softmax and negative sampling, to ensure the reader fully and easily understands the details of how the algorithms function. Combining practical aspects with a more traditional review of the literature, it is directly applicable to a broad readership. It is an invaluable introduction for early graduate students working in natural language processing; a trustworthy guide for industry developers wishing to make use of recent innovations; and a sturdy bridge for researchers already familiar with linguistics or machine learning wishing to understand the other.
Deep Learning In Natural Language Processing
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Author : Li Deng
language : en
Publisher:
Release Date : 2018
Deep Learning In Natural Language Processing written by Li Deng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Artificial Intelligence (incl. Robotics) categories.
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Artificial Intelligence And Natural Language
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Author : Andrey Filchenkov
language : en
Publisher: Springer Nature
Release Date : 2020-09-30
Artificial Intelligence And Natural Language written by Andrey Filchenkov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with Computers categories.
This book constitutes the refereed proceedings of the 9th Conference on Artificial Intelligence and Natural Language, AINL 2020, held in Helsinki, Finland, in October 2020. The 11 revised full papers and 3 short papers were carefully reviewed and selected from 36 submissions. Additionally, the volume presents 1 shared task paper. The volume presents recent research in areas of of text mining, speech technologies, dialogue systems, information retrieval, machine learning, articial intelligence, and robotics.
Artificial Intelligence And Natural Language
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Author : Dmitry Ustalov
language : en
Publisher: Springer
Release Date : 2018-09-28
Artificial Intelligence And Natural Language written by Dmitry Ustalov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-28 with Computers categories.
This book constitutes the refereed proceedings of the 7th Conference on Artificial Intelligence and Natural Language, AINL 2018, held in St. Petersburg, Russia, in October 2018. The 19 revised full papers were carefully reviewed and selected from 56 submissions and cover a wide range of topics, including morphology and word-level semantics, sentence and discourse representations, corpus linguistics, language resources, and social interaction analysis.
Representation Learning For Natural Language Processing
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Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2020-07-03
Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Computers categories.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.