The Complete Guide to Understanding and Using NLP
The Complete Guide to Understanding and Using NLP

Author: Barbara Gibson

Publisher: Atlantic Publishing Company

Published: 2011

Total Pages: 290

ISBN-13: 1601383827

DOWNLOAD EBOOK

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
Practical Natural Language Processing

Author: Sowmya Vajjala

Publisher: O'Reilly Media

Published: 2020-06-17

Total Pages: 455

ISBN-13: 149205402X

DOWNLOAD EBOOK

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 Action
Natural Language Processing in Action

Author: Hannes Hapke

Publisher: Simon and Schuster

Published: 2019-03-16

Total Pages: 798

ISBN-13: 1638356890

DOWNLOAD EBOOK

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)

NLP
NLP

Author: Tom Hoobyar

Publisher: Harper Collins

Published: 2013-02-12

Total Pages: 488

ISBN-13: 0062083627

DOWNLOAD EBOOK

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.

Nlp Workbook: A Practical Guide to Achieving the Results You Want
Nlp Workbook: A Practical Guide to Achieving the Results You Want

Author: Joseph O'Connor

Publisher: Red Wheel/Weiser

Published: 2021-05

Total Pages: 306

ISBN-13: 1590035186

DOWNLOAD EBOOK

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.

Natural Language Processing with Python
Natural Language Processing with Python

Author: Steven Bird

Publisher: "O'Reilly Media, Inc."

Published: 2009-06-12

Total Pages: 506

ISBN-13: 0596555717

DOWNLOAD EBOOK

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.

Getting Started with Natural Language Processing
Getting Started with Natural Language Processing

Author: Ekaterina Kochmar

Publisher: Simon and Schuster

Published: 2022-11-15

Total Pages: 454

ISBN-13: 1638350922

DOWNLOAD EBOOK

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

Introduction to Natural Language Processing
Introduction to Natural Language Processing

Author: Jacob Eisenstein

Publisher: MIT Press

Published: 2019-10-01

Total Pages: 535

ISBN-13: 0262042843

DOWNLOAD EBOOK

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.

Real-World Natural Language Processing
Real-World Natural Language Processing

Author: Masato Hagiwara

Publisher: Simon and Schuster

Published: 2021-12-14

Total Pages: 334

ISBN-13: 1617296422

DOWNLOAD EBOOK

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.

Natural Language Processing with PyTorch
Natural Language Processing with PyTorch

Author: Delip Rao

Publisher: O'Reilly Media

Published: 2019-01-22

Total Pages: 256

ISBN-13: 1491978201

DOWNLOAD EBOOK

Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems