Natural Language Processing In Artificial Intelligence Nlpinai 2021

Author : Roussanka Loukanova
Publisher : Springer Nature
ISBN 13 : 3030901386
Total Pages : 126 pages
Book Rating : 4.87/5 ( download)

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Download or read book Natural Language Processing in Artificial Intelligence — NLPinAI 2021 written by Roussanka Loukanova and published by Springer Nature. This book was released on 2021-11-01 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers theoretical work, approaches, applications, and techniques for computational models of information, language, and reasoning. Computational and technological developments that incorporate natural language are proliferating. Adequate coverage of natural language processing in artificial intelligence encounters problems on developments of specialized computational approaches and algorithms. Many difficulties are due to ambiguities in natural language and dependency of interpretations on contexts and agents. Classical approaches proceed with relevant updates, and new developments emerge in theories of formal and natural languages, computational models of information and reasoning, and related computerized applications. Its focus is on computational processing of human language and relevant medium languages, which can be theoretically formal, or for programming and specification of computational systems. The goal is to promote intelligent natural language processing, along with models of computation, language, reasoning, and other cognitive processes.

Author : Roussanka Loukanova
Publisher :
ISBN 13 : 9783030901394
Total Pages : 0 pages
Book Rating : 4.94/5 ( download)

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Download or read book Natural Language Processing in Artificial Intelligence - NLPinAI 2021 written by Roussanka Loukanova and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers theoretical work, approaches, applications, and techniques for computational models of information, language, and reasoning. Computational and technological developments that incorporate natural language are proliferating. Adequate coverage of natural language processing in artificial intelligence encounters problems on developments of specialized computational approaches and algorithms. Many difficulties are due to ambiguities in natural language and dependency of interpretations on contexts and agents. Classical approaches proceed with relevant updates, and new developments emerge in theories of formal and natural languages, computational models of information and reasoning, and related computerized applications. Its focus is on computational processing of human language and relevant medium languages, which can be theoretically formal, or for programming and specification of computational systems. The goal is to promote intelligent natural language processing, along with models of computation, language, reasoning, and other cognitive processes.

Author : Roussanka Loukanova
Publisher : Springer Nature
ISBN 13 : 3030637875
Total Pages : 250 pages
Book Rating : 4.73/5 ( download)

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Download or read book Natural Language Processing in Artificial Intelligence—NLPinAI 2020 written by Roussanka Loukanova and published by Springer Nature. This book was released on 2021-03-25 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers theoretical work, applications, approaches, and techniques for computational models of information and its presentation by language (artificial, human, or natural in other ways). Computational and technological developments that incorporate natural language are proliferating. Adequate coverage encounters difficult problems related to ambiguities and dependency on context and agents (humans or computational systems). The goal is to promote computational systems of intelligent natural language processing and related models of computation, language, thought, mental states, reasoning, and other cognitive processes.

Author : Brojo Kishore Mishra
Publisher : CRC Press
ISBN 13 : 1000711315
Total Pages : 297 pages
Book Rating : 4.18/5 ( download)

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Download or read book Natural Language Processing in Artificial Intelligence written by Brojo Kishore Mishra and published by CRC Press. This book was released on 2020-11-01 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.

Author : Ela Kumar
Publisher : I. K. International Pvt Ltd
ISBN 13 : 9380578776
Total Pages : 220 pages
Book Rating : 4.74/5 ( download)

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Download or read book Natural Language Processing written by Ela Kumar and published by I. K. International Pvt Ltd. This book was released on 2013-12-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers all aspects of the area of linguistic analysis and the computational systems that have been developed to perform the language analysis. The book is primarily meant for post graduate and undergraduate technical courses.

Author : Karthiek Reddy Bokka
Publisher : Packt Publishing Ltd
ISBN 13 : 1838553673
Total Pages : 372 pages
Book Rating : 4.78/5 ( download)

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Download or read book Deep Learning for Natural Language Processing written by Karthiek Reddy Bokka and published by Packt Publishing Ltd. This book was released on 2019-06-11 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key FeaturesGain insights into the basic building blocks of natural language processingLearn how to select the best deep neural network to solve your NLP problemsExplore convolutional and recurrent neural networks and long short-term memory networksBook Description Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues. What you will learnUnderstand various pre-processing techniques for deep learning problemsBuild a vector representation of text using word2vec and GloVeCreate a named entity recognizer and parts-of-speech tagger with Apache OpenNLPBuild a machine translation model in KerasDevelop a text generation application using LSTMBuild a trigger word detection application using an attention modelWho this book is for If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.

Author : Li Deng
Publisher : Springer
ISBN 13 : 9811052093
Total Pages : 329 pages
Book Rating : 4.95/5 ( download)

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Download or read book Deep Learning in Natural Language Processing written by Li Deng and published by Springer. This book was released on 2018-05-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : Ankur A. Patel
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492062545
Total Pages : 336 pages
Book Rating : 4.47/5 ( download)

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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

Author : S., Sumathi
Publisher : IGI Global
ISBN 13 : 1799811611
Total Pages : 227 pages
Book Rating : 4.19/5 ( download)

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Download or read book Neural Networks for Natural Language Processing written by S., Sumathi and published by IGI Global. This book was released on 2019-11-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.

Author : Sowmya Vajjala
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492054003
Total Pages : 456 pages
Book Rating : 4.09/5 ( download)

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Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by "O'Reilly Media, Inc.". This book was released on 2020-06-17 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective