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Natural Language Processing in Artificial Intelligence—NLPinAI 2020

Natural Language Processing in Artificial Intelligence—NLPinAI 2020
Author: Roussanka Loukanova
Publisher: Springer Nature
Total Pages: 250
Release: 2021-03-25
Genre: Technology & Engineering
ISBN: 3030637875

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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.


Natural Language Processing in Artificial Intelligence

Natural Language Processing in Artificial Intelligence
Author: Brojo Kishore Mishra
Publisher: CRC Press
Total Pages: 297
Release: 2020-11-01
Genre: Science
ISBN: 1000711315

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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.


Natural Language Processing

Natural Language Processing
Author: Raymond S. T. Lee
Publisher: Springer Nature
Total Pages: 454
Release: 2023-12-16
Genre: Computers
ISBN: 9819919991

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This textbook presents an up-to-date and comprehensive overview of Natural Language Processing (NLP), from basic concepts to core algorithms and key applications. Further, it contains seven step-by-step NLP workshops (total length: 14 hours) offering hands-on practice with essential Python tools like NLTK, spaCy, TensorFlow Kera, Transformer and BERT. The objective of this book is to provide readers with a fundamental grasp of NLP and its core technologies, and to enable them to build their own NLP applications (e.g. Chatbot systems) using Python-based NLP tools. It is both a textbook and NLP tool-book intended for the following readers: undergraduate students from various disciplines who want to learn NLP; lecturers and tutors who want to teach courses or tutorials for undergraduate/graduate students on NLP and related AI topics; and readers with various backgrounds who want to learn NLP, and more importantly, to build workable NLP applications after completing its 14 hours of Python-based workshops.


Deep Learning in Natural Language Processing

Deep Learning in Natural Language Processing
Author: Li Deng
Publisher: Springer
Total Pages: 329
Release: 2018-05-23
Genre: Computers
ISBN: 9811052093

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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.


Ethical Challenges in Cancer Diagnosis and Therapy

Ethical Challenges in Cancer Diagnosis and Therapy
Author: Axel Bauer
Publisher:
Total Pages: 290
Release: 2021
Genre: Cancer
ISBN: 9783030637880

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"This book presents in detail the problems and ethical challenges in daily oncological practice. In western industrialized countries, roughly 25 percent of all citizens still die from cancer. Despite significant progress in basic science and in individual areas of clinical care, even in the 21st century, being diagnosed with cancer has lost none of its dread and can still be a death sentence. This situation raises many problems and challenges for medical ethics, e.g., the question of the benefits and risks of prevention programs, or the right to know and not to know. Clinical trials with cancer patients and quality assurance for surgery, radiotherapy and medication also pose a series of ethical dilemmas. Furthermore, cancer treatment is a psychological challenge not only for patients but also for physicians and caregivers. The issues of adequate pain management and good palliative care, of treatment limiting and the question of assisted suicide at the end of life also have to be considered. In order to reflect the subject's diverse and multifaceted nature, the book incorporates legal, ethnographic, historical and literary perspectives into ethical considerations"--Publisher's description.


Natural Language Processing in Artificial Intelligence — NLPinAI 2021

Natural Language Processing in Artificial Intelligence — NLPinAI 2021
Author: Roussanka Loukanova
Publisher: Springer Nature
Total Pages: 126
Release: 2021-11-01
Genre: Technology & Engineering
ISBN: 3030901386

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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.


Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing
Author: Karthiek Reddy Bokka
Publisher: Packt Publishing Ltd
Total Pages: 372
Release: 2019-06-11
Genre: Computers
ISBN: 1838553673

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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.


Handbook of Natural Language Processing

Handbook of Natural Language Processing
Author: Robert Dale
Publisher: CRC Press
Total Pages: 974
Release: 2000-07-25
Genre: Business & Economics
ISBN: 9780824790004

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This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.


Natural Language Processing

Natural Language Processing
Author: Ela Kumar
Publisher: I. K. International Pvt Ltd
Total Pages: 220
Release: 2013-12-30
Genre: Computers
ISBN: 9380578776

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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.


Introduction to Natural Language Processing

Introduction to Natural Language Processing
Author: Michael Walker
Publisher:
Total Pages: 76
Release: 2017-08-04
Genre:
ISBN: 9781724811745

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***BUY NOW (Will soon return to 19.59) ******Free eBook for customers who purchase the print book from Amazon*** Are you thinking of learning more about Natural Language Processing (NLP)? This book is for you. It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using ]NLP. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses. To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of Data Science and NLP. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Introduction to Natural Language Processing What is Natural Language Processing Perspectivizing NLP: Areas of AI and Their Interdependencies Purpose of Natural Language Processing Text Manipulation Tokenization Stemming Lemmatization Normalization Accessing Text Corpora and Lexical Resources Processing Raw Text Categorizing and Tagging Words NLP Applications Text Classification Sentiment Classification Topic Modelling Question Answering Speech Recognition Machine Translation Word Representation Bag of Words One-Hot Encoding Word Vectors Representation Word2Vec and GloVe Learning to Classify Text Supervised Classification Decision Trees Naive Bayes Classifiers Maximum Entropy Classifiers Deep Learning for NLP What is Deep Learning Feed Forward Neural Networks Recurrent Neural Networks Gated Recurrent Unit Long Short Term Memory Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: If you want to smash NLP concepts and Fundamentals for Beginners from scratch, this book is for you. No need for any coding experience. Q: Does this book include everything I need to become a NLP expert? A: Unfortunately, no. This book is designed for readers taking their first steps in NLP and further learning will be required beyond this book to master all aspects of NLP. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at [email protected]. If you need to see the quality of our job, AI Sciences Company offering you a free eBook in Machine Learning with Python written by the data scientist Alain Kaufmann at http: //aisciences.net/free-books/