Understanding Nlp

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Natural Language Processing in Action

Author : Hannes Hapke
Publisher : Simon and Schuster
ISBN 13 : 1638356890
Total Pages : 798 pages
Book Rating : 4.6/5 (383 download)

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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)

Understanding NLP

Author : Neilson Kite
Publisher : Kogan Page Publishers
ISBN 13 : 0749463821
Total Pages : 232 pages
Book Rating : 4.7/5 (494 download)

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Book Synopsis Understanding NLP by : Neilson Kite

Download or read book Understanding NLP written by Neilson Kite and published by Kogan Page Publishers. This book was released on 2011-11-03 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you ever wondered how some people constantly achieve success in the workplace and in everyday life? Do you wish you knew more about how they think and behave? Understanding NLP will take you a step closer to sharing their success by showing you how to achieve personal and organizational goals. By applying the principles of NLP to the working environment and describing familiar situations in jargon-free language, it provides insights into interpersonal differences, selling and negotiation, influencing skills and the use of language. Further simplifying the key concepts of NLP and with greater emphasis on the differences between rapport and relationship and how both can be better developed and managed, Understanding NLP provides even more clarity and guidance in a simple and common sense way, helping you to make radical changes in the way you approach people, life and work.

The Complete Guide to Understanding and Using NLP

Author : Barbara Gibson
Publisher : Atlantic Publishing Company
ISBN 13 : 1601383827
Total Pages : 290 pages
Book Rating : 4.6/5 (13 download)

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Book Synopsis The Complete Guide to Understanding and Using NLP by : Barbara Gibson

Download or read book The Complete Guide to Understanding and Using NLP written by Barbara Gibson and published by Atlantic Publishing Company. This book was released on 2011 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it first developed in the 1970s by Richard Bandler and John Grinder, Neuro-Linguistic Programming or NLP was considered a great advancement in psychotherapy and was widely studied as a means by which to subjectively study language, communication and personal change. Today, it is a highly successful means by which individuals such as yourself can not only get better in touch with yourself and how you interact with the world through language and other forms of communication, but to better understand those around you and make enhanced decisions, provide advice, and boost yourself image through understanding. This book was written to assist every individual who ever wanted to become more in tune with their minds and their interactions with peers, family, and friends. You will learn what NLP is and when it was first developed along with the basic studies originally published in the early 1970s. You will learn how to start reading through and understanding maps and filters, the basics of learning, unlearning and relearning and how communication and language are the fundamental basis for essentially every action you take in life. You will learn how to control pacing and leading in communication, what perception involves and how to understand the various representational systems described by NLP. You will learn how to recognize predicates of conversation and eye accessing cues as well as how to recognize and work with various physiological states and emotional freedom. You will learn the basics of elicitation and anchors, including resource anchoring, collapsing anchoring, and future pacing. Top psychologist and therapists have been interviewed for this guide, with dozens providing information on which aspects of NLP are most effective for each individual. Using their advice as a map, you will learn how to use loops and systems and understand the different levels of learning. Everything from how language sets limits on your experience to how meta model patterns control you life will be discussed in detail to help you take control of your life through understanding of Neuro-Linguistic Programming. Atlantic Publishing is a small, independent publishing company based in Ocala, Florida. Founded over twenty years ago in the company president's garage, Atlantic Publishing has grown to become a renowned resource for non-fiction books. Today, over 450 titles are in print covering subjects such as small business, healthy living, management, finance, careers, and real estate. Atlantic Publishing prides itself on producing award winning, high-quality manuals that give readers up-to-date, pertinent information, real-world examples, and case studies with expert advice. Every book has resources, contact information, and web sites of the products or companies discussed.

Practical Natural Language Processing

Author : Sowmya Vajjala
Publisher : O'Reilly Media
ISBN 13 : 149205402X
Total Pages : 455 pages
Book Rating : 4.4/5 (92 download)

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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

Natural Language Processing in Artificial Intelligence

Author : Brojo Kishore Mishra
Publisher : CRC Press
ISBN 13 : 1000711315
Total Pages : 297 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Natural Language Processing in Artificial Intelligence by : Brojo Kishore Mishra

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.

Applied Natural Language Processing in the Enterprise

Author : Ankur A. Patel
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492062545
Total Pages : 336 pages
Book Rating : 4.4/5 (92 download)

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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

Understanding NLP

Author : Peter Young
Publisher : Crown House Publishing
ISBN 13 : 1845906691
Total Pages : 241 pages
Book Rating : 4.8/5 (459 download)

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Book Synopsis Understanding NLP by : Peter Young

Download or read book Understanding NLP written by Peter Young and published by Crown House Publishing. This book was released on 2003-09-18 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding NLP opens a doorway into a more imaginative and coherent way of understanding and using NLP. This completely revised edition unites the many strands of NLP using an elegant paradigm which Peter Young calls the Six Perceptual Positions model. The book provides numerous examples of the paradigm in practice.

Natural Language Processing

Author : Yue Zhang
Publisher : Cambridge University Press
ISBN 13 : 1108420214
Total Pages : 487 pages
Book Rating : 4.1/5 (84 download)

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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.

Natural Language Processing with Python

Author : Steven Bird
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 0596555717
Total Pages : 506 pages
Book Rating : 4.5/5 (965 download)

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Book Synopsis Natural Language Processing with Python by : Steven Bird

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.

Natural Language Processing with Spark NLP

Author : Alex Thomas
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492047716
Total Pages : 411 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Natural Language Processing with Spark NLP by : Alex Thomas

Download or read book Natural Language Processing with Spark NLP written by Alex Thomas and published by "O'Reilly Media, Inc.". This book was released on 2020-06-25 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to build an enterprise-quality application that uses natural language text but aren’t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. You’ll also explore special concerns for developing text-based applications, such as performance. In four sections, you’ll learn NLP basics and building blocks before diving into application and system building: Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning Building blocks: Learn techniques for building NLP applications—including tokenization, sentence segmentation, and named-entity recognition—and discover how and why they work Applications: Explore the design, development, and experimentation process for building your own NLP applications Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support

Foundations of Statistical Natural Language Processing

Author : Christopher Manning
Publisher : MIT Press
ISBN 13 : 0262303795
Total Pages : 719 pages
Book Rating : 4.2/5 (623 download)

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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.

Naive Semantics for Natural Language Understanding

Author : Kathleen Dahlgren
Publisher : Springer Science & Business Media
ISBN 13 : 146131075X
Total Pages : 261 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Naive Semantics for Natural Language Understanding by : Kathleen Dahlgren

Download or read book Naive Semantics for Natural Language Understanding written by Kathleen Dahlgren and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a theory, Naive Semantics (NS), a theory of the knowledge underlying natural language understanding. The basic assumption of NS is that knowing what a word means is not very different from knowing anything else, so that there is no difference in form of cognitive representation between lexical semantics and ency clopedic knowledge. NS represents word meanings as commonsense knowledge, and builds no special representation language (other than elements of first-order logic). The idea of teaching computers common sense knowledge originated with McCarthy and Hayes (1969), and has been extended by a number of researchers (Hobbs and Moore, 1985, Lenat et aI, 1986). Commonsense knowledge is a set of naive beliefs, at times vague and inaccurate, about the way the world is structured. Traditionally, word meanings have been viewed as criterial, as giving truth conditions for membership in the classes words name. The theory of NS, in identifying word meanings with commonsense knowledge, sees word meanings as typical descriptions of classes of objects, rather than as criterial descriptions. Therefore, reasoning with NS represen tations is probabilistic rather than monotonic. This book is divided into two parts. Part I elaborates the theory of Naive Semantics. Chapter 1 illustrates and justifies the theory. Chapter 2 details the representation of nouns in the theory, and Chapter 4 the verbs, originally published as "Commonsense Reasoning with Verbs" (McDowell and Dahlgren, 1987). Chapter 3 describes kind types, which are naive constraints on noun representations.

Deep Learning in Natural Language Processing

Author : Li Deng
Publisher : Springer
ISBN 13 : 9811052093
Total Pages : 329 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Deep Learning in Natural Language Processing by : Li Deng

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.

Introduction to Natural Language Processing

Author : Jacob Eisenstein
Publisher : MIT Press
ISBN 13 : 0262042843
Total Pages : 535 pages
Book Rating : 4.2/5 (62 download)

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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.

Integration of World Knowledge for Natural Language Understanding

Author : Ekaterina Ovchinnikova
Publisher : Springer Science & Business Media
ISBN 13 : 9491216538
Total Pages : 242 pages
Book Rating : 4.4/5 (912 download)

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Book Synopsis Integration of World Knowledge for Natural Language Understanding by : Ekaterina Ovchinnikova

Download or read book Integration of World Knowledge for Natural Language Understanding written by Ekaterina Ovchinnikova and published by Springer Science & Business Media. This book was released on 2012-02-15 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concerns non-linguistic knowledge required to perform computational natural language understanding (NLU). The main objective of the book is to show that inference-based NLU has the potential for practical large scale applications. First, an introduction to research areas relevant for NLU is given. We review approaches to linguistic meaning, explore knowledge resources, describe semantic parsers, and compare two main forms of inference: deduction and abduction. In the main part of the book, we propose an integrative knowledge base combining lexical-semantic, ontological, and distributional knowledge. A particular attention is payed to ensuring its consistency. We then design a reasoning procedure able to make use of the large scale knowledge base. We experiment both with a deduction-based NLU system and with an abductive reasoner. For evaluation, we use three different NLU tasks: recognizing textual entailment, semantic role labeling, and interpretation of noun dependencies.

Natural Language Understanding

Author : James Allen
Publisher : Pearson
ISBN 13 :
Total Pages : 680 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Natural Language Understanding by : James Allen

Download or read book Natural Language Understanding written by James Allen and published by Pearson. This book was released on 1995 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a leading authority in artificial intelligence, this book delivers a synthesis of the major modern techniques and the most current research in natural language processing. The approach is unique in its coverage of semantic interpretation and discourse alongside the foundational material in syntactic processing.

Deep Learning for Natural Language Processing

Author : Stephan Raaijmakers
Publisher : Simon and Schuster
ISBN 13 : 1638353999
Total Pages : 294 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning for Natural Language Processing by : Stephan Raaijmakers

Download or read book Deep Learning for Natural Language Processing written by Stephan Raaijmakers and published by Simon and Schuster. This book was released on 2022-12-20 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Inside Deep Learning for Natural Language Processing you’ll find a wealth of NLP insights, including: An overview of NLP and deep learning One-hot text representations Word embeddings Models for textual similarity Sequential NLP Semantic role labeling Deep memory-based NLP Linguistic structure Hyperparameters for deep NLP Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. About the technology Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. About the book Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You’ll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses! What's inside Improve question answering with sequential NLP Boost performance with linguistic multitask learning Accurately interpret linguistic structure Master multiple word embedding techniques About the reader For readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required. About the author Stephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO). Table of Contents PART 1 INTRODUCTION 1 Deep learning for NLP 2 Deep learning and language: The basics 3 Text embeddings PART 2 DEEP NLP 4 Textual similarity 5 Sequential NLP 6 Episodic memory for NLP PART 3 ADVANCED TOPICS 7 Attention 8 Multitask learning 9 Transformers 10 Applications of Transformers: Hands-on with BERT