Download or read book NLP written by Tom Hoobyar and published by Harper Collins. This book was released on 2013-02-12 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: By the team behind the bestselling NLP: The New Technology of Achievement comes an essential new guide to NLP techniques—for self-development and influencing others—in a focused, step-by-step handbook. NLP (Neuro-Linguistic Programming) has already helped millions of people overcome fears, increase confidence, enrich relationships, and achieve greater success. Now, from the company and training team behind NLP: The New Technology of Achievement, one of the bestselling NLP books of all time, comes NLP: The Essential Guide to Neuro-Linguistic Programming \. Written by three NLP Master Practitioners and training coaches, including the president of NLP Comprehensive, with an introduction from the President of NLP Comprehensive, NLP: The Essential Guide to Neuro-Linguistic Programming guides users to peak performance in business and life, and gets specific results. In twelve illuminating sections, NLP: The Essential Guide to Neuro-Linguistic Programming leads you through dozens of “discoveries”—revelations of NLP practice that enable you to explore your own personal thinking patterns, to manage them—and to transform them. Divided into two categories, “All About You” and “All About the Other Guy,” these strategies offer a personal and interpersonal program that frees you to become better at managing your feelings instead of being dominated by them, managing your motivations, being less judgmental, more productive, more confident, more flexible, more persuasive, liked, and respected. Chapters on “Personal Remodeling” (Discovery 9: No inner enemy) and “Secrets of Making Your Point” (Discovery 31: Convey understanding and safety without talking), enhance creativity, collaboration, cooperation, and communication. Through “mind reading” techniques—non-verbal communication, and “hearing what’s missing”—learn the secrets of relating with others, understanding how they are thinking—and influencing them. A streamlined all-purpose guide for both newcomers and NLP veterans, NLP: The Essential Guide to Neuro-Linguistic Programming is the new all-in-one, eye-opening blueprint for your own ultimate success.

Download or read book NLP written by Tom Hoobyar and published by William Morrow Paperbacks. This book was released on 2013-01-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: NLP (Neuro-Linguistic Programming) has helped millions to overcome their fears, increase their confidence, and achieve greater success in their personal and professional lives and relationships. Now, from the company that created NLP: The New Technology of Achievement—one of the bestselling NLP books of all time—comes NLP: The Essential Guide to Neuro-Linguistic Programming. This user-friendly guide, written by three seasoned NLP Master Practitioners and coaches, leads you on a personal journey in using and applying NLP in everyday life. Through their real-life stories, you will experience the NLP strategies you need to achieve specific results in business and in life. As you read NLP: The Essential Guide, you'll find yourself thinking in new ways and applying the techniques to your own personal challenges and opportunities for greater satisfaction.

Download or read book Linguistic Fundamentals for Natural Language Processing written by Emily M. Bender and published by Morgan & Claypool Publishers. This book was released on 2013-06-01 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages

Download or read book Essential NLP written by Amanda Vickers and published by Teach Yourself. This book was released on 2010-02-26 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of a popular guide to Neuro-Linguistic Programming draws on the latest neuroscience findings to give you a better understanding of NLP, and what it can do for you both professionally and personally. It introduces the foundations of NLP and the key principles of the technique, explaining the theory behind submodalities, the power of beliefs and values, and the importance of well-formed outcomes. Written in a jargon-free and accessible style, it will help you to use rapport, modelling and other effective strategies to achieve your goals at work - and to bring the principles of NLP to other areas in your life, making you an effective leader, partner and negotiator.

Download or read book NLP For Beginners written by Shlomo Vaknin and published by Independently Published. This book was released on 2021-08-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're only beginning to explore NLP, this book will give you a solid foundation for the subject, and then some. You will explore all the essentials in short and practical learning modules, such as: - What is NLP? VAK? Rep system? Anchor? Framing? Re-framing?! Eye AccessingCues? Modalities What Sub-Modalities? Presuppositions? etc.- Behavioral & Symbolic mirroring- How Will I Actually Create Rapport?- How Do You Chain Anchors? (in order to change a behavior)- The key elements of modeling, and: - Once You Have a Model, What Do You Do With It?- What is Conversational Hypnosis? How to use it?-... and much more. For a more in-depth look into NLP concepts, read the books NLP: Start Here and The Big Book of NLP, Expanded.

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 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 NLP Workbook written by Joseph O'Connor and published by Conari Press. This book was released on 2012-12-01 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuro-Linguistic Programming (NLP) studies brilliance and quality—how outstanding individuals and organizations get their outstanding results. Joseph O’Conner, a leading international NLP trainer and co-author of the bestselling Introducing NLP, offers a step-by-step guide to learning the NLP methods and techniques to help you become the person you want to be in the NLP Workbook. The NLP Workbook is a complete guide to NLP that includes: How to create and achieve outcomes How to choose your emotional state and shift thinking Meta modeling your own internal dialogue All of the basic NLP techniques and training exercises An Action Plan with exercises and suggestions for skill-building O’Conner discusses a range of topics from rapport and trust, and how to visualize, to negotiation skills, mental rehearsal and coaching. NLP Workbook is a book for everyone and anyone interested in NLP. The neophyte will find definitions, examples, and a step-by-step entry into learning how to use NLP, and trainers will discover many new ideas for NLP training.

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

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 The Ultimate Introduction to NLP How to build a successful life written by Richard Bandler and published by HarperCollins UK. This book was released on 2013-01-03 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Richard Bandler, co-creator of NLP and the man who inspired Paul McKenna to greatness, collaborates with Alessio Roberti and Owen Fitzpatrick to reveal how to unleash your true potential and transform your life.

Download or read book Natural Language Processing Fundamentals written by Sohom Ghosh and published by Packt Publishing Ltd. This book was released on 2019-03-30 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key FeaturesAssimilate key NLP concepts and terminologies Explore popular NLP tools and techniquesGain practical experience using NLP in application codeBook Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learnObtain, verify, and clean data before transforming it into a correct format for usePerform data analysis and machine learning tasks using PythonUnderstand the basics of computational linguisticsBuild models for general natural language processing tasksEvaluate the performance of a model with the right metricsVisualize, quantify, and perform exploratory analysis from any text dataWho this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.

Download or read book Leading With NLP Essential Leadership Skills for Influencing and Managing People written by Joseph O’Connor and published by HarperCollins UK. This book was released on 2013-07-04 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Leadership Skills for Influencing and Managing People

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.

Download or read book Linguistic Fundamentals for Natural Language Processing II written by Emily M. Bender and published by Morgan & Claypool Publishers. This book was released on 2019-11-06 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed by what is known about how humans use language to express and understand communicative intents. The purpose of this book is to present a selection of useful information about semantics and pragmatics, as understood in linguistics, in a way that's accessible to and useful for NLP practitioners with minimal (or even no) prior training in linguistics.

Download or read book Natural Language Processing with Transformers Revised Edition written by Lewis Tunstall and published by "O'Reilly Media, Inc.". This book was released on 2022-05-26 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments

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