Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Exploring Natural Language
Download Exploring Natural Language full books in PDF, epub, and Kindle. Read online Exploring Natural Language ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Exploring Natural Language by : Gerald Nelson
Download or read book Exploring Natural Language written by Gerald Nelson and published by John Benjamins Publishing. This book was released on 2002 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: ICE-GB is a 1 million-word corpus of contemporary British English. It is fully parsed, and contains over 83,000 syntactic trees. Together with the dedicated retrieval software, ICECUP, ICE-GB is an unprecedented resource for the study of English syntax.Exploring Natural Language is a comprehensive guide to both corpus and software. It contains a full reference for ICE-GB. The chapters on ICECUP provide complete instructions on the use of the many features of the software, including concordancing, lexical and grammatical searches, sociolinguistic queries, random sampling, and searching for syntactic structures using ICECUP's Fuzzy Tree Fragment models. Special attention is given to the principles of experimental design in a parsed corpus.Six case studies provide step-by-step illustrations of how the corpus and software can be used to explore real linguistic issues, from simple lexical studies to more complex syntactic topics, such as noun phrase structure, verb transitivity, and voice.
Book Synopsis Spotting and Discovering Terms Through Natural Language Processing by : Christian Jacquemin
Download or read book Spotting and Discovering Terms Through Natural Language Processing written by Christian Jacquemin and published by MIT Press. This book was released on 2001 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: The acquired parsed terms can then be applied for precise retrieval and assembly of information."--BOOK JACKET.
Book Synopsis Exploring Natural Language by : Gerald Nelson
Download or read book Exploring Natural Language written by Gerald Nelson and published by John Benjamins Publishing. This book was released on 2002-06-27 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: ICE-GB is a 1 million-word corpus of contemporary British English. It is fully parsed, and contains over 83,000 syntactic trees. Together with the dedicated retrieval software, ICECUP, ICE-GB is an unprecedented resource for the study of English syntax.Exploring Natural Language is a comprehensive guide to both corpus and software. It contains a full reference for ICE-GB. The chapters on ICECUP provide complete instructions on the use of the many features of the software, including concordancing, lexical and grammatical searches, sociolinguistic queries, random sampling, and searching for syntactic structures using ICECUP's Fuzzy Tree Fragment models. Special attention is given to the principles of experimental design in a parsed corpus. Six case studies provide step-by-step illustrations of how the corpus and software can be used to explore real linguistic issues, from simple lexical studies to more complex syntactic topics, such as noun phrase structure, verb transitivity, and voice.
Book Synopsis Getting Started with Natural Language Processing by : Ekaterina Kochmar
Download or read book Getting Started with Natural Language Processing written by Ekaterina Kochmar and published by Simon and Schuster. This book was released on 2022-11-15 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hit the ground running with this in-depth introduction to the NLP skills and techniques that allow your computers to speak human. In Getting Started with Natural Language Processing you’ll learn about: Fundamental concepts and algorithms of NLP Useful Python libraries for NLP Building a search algorithm Extracting information from raw text Predicting sentiment of an input text Author profiling Topic labeling Named entity recognition Getting Started with Natural Language Processing is an enjoyable and understandable guide that helps you engineer your first NLP algorithms. Your tutor is Dr. Ekaterina Kochmar, lecturer at the University of Bath, who has helped thousands of students take their first steps with NLP. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. If you’re a beginner to NLP and want to upgrade your applications with functions and features like information extraction, user profiling, and automatic topic labeling, this is the book for you. About the technology From smart speakers to customer service chatbots, apps that understand text and speech are everywhere. Natural language processing, or NLP, is the key to this powerful form of human/computer interaction. And a new generation of tools and techniques make it easier than ever to get started with NLP! About the book Getting Started with Natural Language Processing teaches you how to upgrade user-facing applications with text and speech-based features. From the accessible explanations and hands-on examples in this book you’ll learn how to apply NLP to sentiment analysis, user profiling, and much more. As you go, each new project builds on what you’ve previously learned, introducing new concepts and skills. Handy diagrams and intuitive Python code samples make it easy to get started—even if you have no background in machine learning! What's inside Fundamental concepts and algorithms of NLP Extracting information from raw text Useful Python libraries Topic labeling Building a search algorithm About the reader You’ll need basic Python skills. No experience with NLP required. About the author Ekaterina Kochmar is a lecturer at the Department of Computer Science of the University of Bath, where she is part of the AI research group. Table of Contents 1 Introduction 2 Your first NLP example 3 Introduction to information search 4 Information extraction 5 Author profiling as a machine-learning task 6 Linguistic feature engineering for author profiling 7 Your first sentiment analyzer using sentiment lexicons 8 Sentiment analysis with a data-driven approach 9 Topic analysis 10 Topic modeling 11 Named-entity recognition
Book Synopsis Hands-On Python Natural Language Processing by : Aman Kedia
Download or read book Hands-On Python Natural Language Processing written by Aman Kedia and published by Packt Publishing Ltd. This book was released on 2020-06-26 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get well-versed with traditional as well as modern natural language processing concepts and techniques Key FeaturesPerform various NLP tasks to build linguistic applications using Python librariesUnderstand, analyze, and generate text to provide accurate resultsInterpret human language using various NLP concepts, methodologies, and toolsBook Description Natural Language Processing (NLP) is the subfield in computational linguistics that enables computers to understand, process, and analyze text. This book caters to the unmet demand for hands-on training of NLP concepts and provides exposure to real-world applications along with a solid theoretical grounding. This book starts by introducing you to the field of NLP and its applications, along with the modern Python libraries that you'll use to build your NLP-powered apps. With the help of practical examples, you’ll learn how to build reasonably sophisticated NLP applications, and cover various methodologies and challenges in deploying NLP applications in the real world. You'll cover key NLP tasks such as text classification, semantic embedding, sentiment analysis, machine translation, and developing a chatbot using machine learning and deep learning techniques. The book will also help you discover how machine learning techniques play a vital role in making your linguistic apps smart. Every chapter is accompanied by examples of real-world applications to help you build impressive NLP applications of your own. By the end of this NLP book, you’ll be able to work with language data, use machine learning to identify patterns in text, and get acquainted with the advancements in NLP. What you will learnUnderstand how NLP powers modern applicationsExplore key NLP techniques to build your natural language vocabularyTransform text data into mathematical data structures and learn how to improve text mining modelsDiscover how various neural network architectures work with natural language dataGet the hang of building sophisticated text processing models using machine learning and deep learningCheck out state-of-the-art architectures that have revolutionized research in the NLP domainWho this book is for This NLP Python book is for anyone looking to learn NLP’s theoretical and practical aspects alike. It starts with the basics and gradually covers advanced concepts to make it easy to follow for readers with varying levels of NLP proficiency. This comprehensive guide will help you develop a thorough understanding of the NLP methodologies for building linguistic applications; however, working knowledge of Python programming language and high school level mathematics is expected.
Book Synopsis Introduction to Natural Language Processing by : Jacob Eisenstein
Download or read book Introduction to Natural Language Processing written by Jacob Eisenstein and published by MIT Press. This book was released on 2019-10-01 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques. This textbook provides a technical perspective on natural language processing—methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation. The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.
Book Synopsis Natural Language Processing and Computational Linguistics by : Bhargav Srinivasa-Desikan
Download or read book Natural Language Processing and Computational Linguistics written by Bhargav Srinivasa-Desikan and published by Packt Publishing Ltd. This book was released on 2018-06-29 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!
Book Synopsis Natural Language Processing for Online Applications by : Peter Jackson
Download or read book Natural Language Processing for Online Applications written by Peter Jackson and published by John Benjamins Publishing. This book was released on 2007-06-05 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns. It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues. Current research topics are covered only to the extent that they are informing current applications; detailed coverage of longer term research and more theoretical treatments should be sought elsewhere. There are many pointers at the ends of the chapters that the reader can follow to explore the literature. However, the book does maintain a strong emphasis on evaluation in every chapter both in terms of methodology and the results of controlled experimentation.
Book Synopsis Applied Natural Language Processing in the Enterprise by : Ankur A. Patel
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
Book Synopsis Natural Language Processing in Action by : Hannes Hapke
Download or read book Natural Language Processing in Action written by Hannes Hapke and published by Simon and Schuster. This book was released on 2019-03-16 with total page 798 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing)
Book Synopsis Natural Language Processing by : Yue Zhang
Download or read book Natural Language Processing written by Yue Zhang and published by Cambridge University Press. This book was released on 2021-01-07 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.
Book Synopsis Practical Natural Language Processing by : Sowmya Vajjala
Download or read book Practical Natural Language Processing written by Sowmya Vajjala and published by O'Reilly Media. This book was released on 2020-06-17 with total page 455 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
Book Synopsis Handbook of Natural Language Processing by : Robert Dale
Download or read book Handbook of Natural Language Processing written by Robert Dale and published by CRC Press. This book was released on 2000-07-25 with total page 1015 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Real-World Natural Language Processing by : Masato Hagiwara
Download or read book Real-World Natural Language Processing written by Masato Hagiwara and published by Simon and Schuster. This book was released on 2021-12-14 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken. Real-world Natural Language Processing teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you''ll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technology Natural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you''ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you''ll use in all different kinds of NLP programs. By the time you''re done, you''ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems. what''s inside Design, develop, and deploy basic NLP applications NLP libraries such as AllenNLP and Fairseq Advanced NLP concepts such as attention and transfer learning about the reader Aimed at intermediate Python programmers. No mathematical or machine learning knowledge required. about the author Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.
Book Synopsis Foundations of Statistical Natural Language Processing by : Christopher Manning
Download or read book Foundations of Statistical Natural Language Processing written by Christopher Manning and published by MIT Press. This book was released on 1999-05-28 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Cognitive Approach to Natural Language Processing by : Bernadette Sharp
Download or read book Cognitive Approach to Natural Language Processing written by Bernadette Sharp and published by Elsevier. This book was released on 2017-05-31 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: As natural language processing spans many different disciplines, it is sometimes difficult to understand the contributions and the challenges that each of them presents. This book explores the special relationship between natural language processing and cognitive science, and the contribution of computer science to these two fields. It is based on the recent research papers submitted at the international workshops of Natural Language and Cognitive Science (NLPCS) which was launched in 2004 in an effort to bring together natural language researchers, computer scientists, and cognitive and linguistic scientists to collaborate together and advance research in natural language processing. The chapters cover areas related to language understanding, language generation, word association, word sense disambiguation, word predictability, text production and authorship attribution. This book will be relevant to students and researchers interested in the interdisciplinary nature of language processing. - Discusses the problems and issues that researchers face, providing an opportunity for developers of NLP systems to learn from cognitive scientists, cognitive linguistics and neurolinguistics - Provides a valuable opportunity to link the study of natural language processing to the understanding of the cognitive processes of the brain
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1799809528 Total Pages :1704 pages Book Rating :4.7/5 (998 download)
Book Synopsis Natural Language Processing: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Natural Language Processing: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-11-01 with total page 1704 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology continues to become more sophisticated, a computer’s ability to understand, interpret, and manipulate natural language is also accelerating. Persistent research in the field of natural language processing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror natural language processes that have existed for centuries. Natural Language Processing: Concepts, Methodologies, Tools, and Applications is a vital reference source on the latest concepts, processes, and techniques for communication between computers and humans. Highlighting a range of topics such as machine learning, computational linguistics, and semantic analysis, this multi-volume book is ideally designed for computer engineers, computer and software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of natural language processing.
