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.

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

Download or read book Transfer Learning for Natural Language Processing written by Paul Azunre and published by Simon and Schuster. This book was released on 2021-08-31 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build custom NLP models in record time by adapting pre-trained machine learning models to solve specialized problems. Summary In Transfer Learning for Natural Language Processing you will learn: Fine tuning pretrained models with new domain data Picking the right model to reduce resource usage Transfer learning for neural network architectures Generating text with generative pretrained transformers Cross-lingual transfer learning with BERT Foundations for exploring NLP academic literature Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you’ll save on training time and computational costs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. About the book Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions quickly by building on existing pretrained models. This instantly useful book provides crystal-clear explanations of the concepts you need to grok transfer learning along with hands-on examples so you can practice your new skills immediately. As you go, you’ll apply state-of-the-art transfer learning methods to create a spam email classifier, a fact checker, and more real-world applications. What's inside Fine tuning pretrained models with new domain data Picking the right model to reduce resource use Transfer learning for neural network architectures Generating text with pretrained transformers About the reader For machine learning engineers and data scientists with some experience in NLP. About the author Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. Table of Contents PART 1 INTRODUCTION AND OVERVIEW 1 What is transfer learning? 2 Getting started with baselines: Data preprocessing 3 Getting started with baselines: Benchmarking and optimization PART 2 SHALLOW TRANSFER LEARNING AND DEEP TRANSFER LEARNING WITH RECURRENT NEURAL NETWORKS (RNNS) 4 Shallow transfer learning for NLP 5 Preprocessing data for recurrent neural network deep transfer learning experiments 6 Deep transfer learning for NLP with recurrent neural networks PART 3 DEEP TRANSFER LEARNING WITH TRANSFORMERS AND ADAPTATION STRATEGIES 7 Deep transfer learning for NLP with the transformer and GPT 8 Deep transfer learning for NLP with BERT and multilingual BERT 9 ULMFiT and knowledge distillation adaptation strategies 10 ALBERT, adapters, and multitask adaptation strategies 11 Conclusions

Download or read book The Semantic Representation of Natural Language written by Michael Levison and published by A&C Black. This book was released on 2012-12-20 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a detailed, precise and clear semantic formalism designed to allow non-programmers such as linguists and literary specialists to represent elements of meaning which they must deal with in their research and teaching. At the same time, by its basis in a functional programming paradigm, it retains sufficient formal precision to support computational implementation. The formalism is designed to represent meaning as found at a variety of levels, including basic semantic units and relations, word meaning, sentence-level phenomena, and text-level meaning. By drawing on fundamental principles of program design, the proposed formalism is both easy to read and modify yet sufficiently powerful to allow for the representation of complex semantic phenomena. In this monograph, the authors introduce the formalism and show its basic structure, apply it to the analysis of the semantics of a variety of linguistic phenomena in both English and French, and use it to represent the semantics of a variety of texts ranging from single sentences, to textual excepts, to a full story.

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.

Download or read book The Spoken Language Translator written by Manny Rayner and published by Cambridge University Press. This book was released on 2000-08-28 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the Spoken Language Translator (SLT), one of the first major projects in the area of automatic speech translation.

Download or read book Computational Lexical Semantics written by Patrick Saint-Dizier and published by Cambridge University Press. This book was released on 1995-02-24 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lexical semantics has become a major research area within computational linguistics, drawing from psycholinguistics, knowledge representation, and computer algorithms and architecture. Research programs whose goal is the definition of large lexicons are asking what the appropriate representation structure is for different facets of lexical information. Among these facets, semantic information is probably the most complex and the least explored. Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerized lexicons for the automatic treatment of natural language, with applications to machine translation, automatic indexing, and database front-ends, knowledge extraction, among other things. It focuses on semantic issues, as seen by linguists, psychologists, and computer scientists. Besides describing academic research, it also covers ongoing industrial projects.

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.

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.

Download or read book Recent Advances in Natural Language Processing III written by Nicolas Nicolov and published by John Benjamins Publishing. This book was released on 2004-11-30 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume brings together revised versions of a selection of papers presented at the 2003 International Conference on “Recent Advances in Natural Language Processing”. A wide range of topics is covered in the volume: semantics, dialogue, summarization, anaphora resolution, shallow parsing, morphology, part-of-speech tagging, named entity, question answering, word sense disambiguation, information extraction. Various ‘state-of-the-art’ techniques are explored: finite state processing, machine learning (support vector machines, maximum entropy, decision trees, memory-based learning, inductive logic programming, transformation-based learning, perceptions), latent semantic analysis, constraint programming. The papers address different languages (Arabic, English, German, Slavic languages) and use different linguistic frameworks (HPSG, LFG, constraint-based DCG). This book will be of interest to those who work in computational linguistics, corpus linguistics, human language technology, translation studies, cognitive science, psycholinguistics, artificial intelligence, and informatics.

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.

Download or read book Natural Language Processing for Social Media written by Atefeh Farzindar and published by Morgan & Claypool Publishers. This book was released on 2017-12-15 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.

Download or read book Natural Language Processing with Python written by Steven Bird and published by "O'Reilly Media, Inc.". This book was released on 2009-06-12 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

Download or read book Quantification in Natural Languages written by Emmon Bach and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of papers grew out of a research project on "Cross-Linguistic Quantification" originated by Emmon Bach, Angelika Kratzer and Barbara Partee in 1987 at the University of Massachusetts at Amherst, and supported by National Science Foundation Grant BNS 871999. The publication also reflects directly or indirectly several other related activ ities. Bach, Kratzer, and Partee organized a two-evening symposium on cross-linguistic quantification at the 1988 Annual Meeting of the Linguistic Society of America in New Orleans (held without financial support) in order to bring the project to the attention of the linguistic community and solicit ideas and feedback from colleagues who might share our concern for developing a broader typological basis for research in semantics and a better integration of descriptive and theoretical work in the area of quantification in particular. The same trio organized a six-week workshop and open lecture series and related one-day confer ence on the same topic at the 1989 LSA Linguistic Institute at the University of Arizona in Tucson, supported by a supplementary grant, NSF grant BNS-8811250, and Partee offered a seminar on the same topic as part of the Institute course offerings. Eloise Jelinek, who served as a consultant on the principal grant and was a participant in the LSA symposium and the Arizona workshops, joined the group of editors for this volume in 1989.

Download or read book Natural Language Parsing written by David R. Dowty and published by Cambridge University Press. This book was released on 2005-11-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a collection of new papers by leading researchers on natural language parsing. In the past, the problem of how people parse the sentences they hear - determine the identity of the words in these sentences and group these words into larger units - has been addressed in very different ways by experimental psychologists, by theoretical linguists, and by researchers in artificial intelligence, with little apparent relationship among the solutions proposed by each group. However, because of important advances in all these disciplines, research on parsing in each of these fields now seems to have something significant to contribute to the others, as this volume demonstrates. The volume includes some papers applying the results of experimental psychological studies of parsing to linguistic theory, others which present computational models of parsing, and a mathematical linguistics paper on tree-adjoining grammars and parsing.

Download or read book Similar Languages Varieties and Dialects written by Marcos Zampieri and published by Cambridge University Press. This book was released on 2021-09-02 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Studying language variation requires comprehensive interdisciplinary knowledge and new computational tools. This essential reference introduces researchers and graduate students in computer science, linguistics, and NLP to the core topics in language variation and the computational methods applied to similar languages, varieties, and dialects.

Download or read book Embeddings in Natural Language Processing written by Mohammad Taher Pilehvar and published by Morgan & Claypool Publishers. This book was released on 2020-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.