The Origins of NLP brings together the recollections and thoughts of some of the main protagonists from the very early days of NLP. In 1971 Richard Bandler and Frank Pucelik were students at Kresege College at the University of California Santa Cruz. They had a strong mutual interest in Gestalt Therapy, Frank because of his traumatic time in Vietnam and because he had been working with some disaffected and drug-addicted kids, and Richard because he had been working with Science and Behavior Books on transcribing and editing Fritz Perls' seminal work, The Gestalt Approach and Eyewitness to Therapy. They started a local Gestalt group and ran 2-3 sessions a week collaborating and experimenting with the language of therapy. They started achieving some brilliant results but were having problems transferring their skills to others and so Richard invited one of their college professors, John Grinder, to observe what they were doing in order that he would, hopefully, be able to deconstruct what they were doing that was so effective. John was a professor of Linguistics and was instantly impressed with the work that they were doing. He was able to add more structure and in due course the three of them formalised what is now known as the Meta Model. NLP, or Meta as it was known then, was born.

Byron A Lewis MA is the director of the Meta Training Institute, a Northwest Educational and Consulting firm specialising in the techniques of Neuro-Linguistic Programming. Frank Pucelik PhD is widely recognised as one of the world's finest trainers in interpersonal communication and success strategies for change.

Table of Contents: -Content reframing : meaning and context -Negotiating between parts -Creating a new part -Advanced six-step reframing -Reframing systems : couples, families, organizations -Reframing dissociated states : alcoholism, drug abuse, etc.

A collection of activities developed and used with teenagers all over the country that are short, easy to follow and engaging. They can be used as one off activities to spice up a session or can be put together to form one hour lessons or even whole day events. There are suggested combinations of activities to suit different topi such as PSHE, Successful Revision/Learning, SEAL.

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

Why do people have so much difficulty achieving their goals, making big changes, and becoming the people they want to be? If we can imagine it, why can't we achieve it? Transformational NLP: A New Psychology offers a new understanding of how the brain really works and how we can use this knowledge for personal change and growth. Describing the evolution of the brain, Carl Buchheit explains how humans are conditioned by creature-level neurological programming which, while working hard to make sure we survive, also keeps us from expressing ourselves fully in the realms of love and our personal purpose in life. When we want to change our thought and behavior patterns, we find that we are limited by our deeply ingrained habits, our unconscious beliefs, and our self-defined identities. We try a variety of therapies and techniques to overcome limitations, but this rarely works. This book is about who we really are and how our brains really operate. When we understand how our brains work, we can quickly learn to work with and not against ourselves, and change becomes possible. While Transformational NLP has its basis in NLP, and uses many tools of NLP, it has evolved into a very different paradigm. The book investigates the history of NLP, from its intellectual antecedents in the science and philosophies of Alfred Korzybski and Noam Chomsky to the ground-breaking work of John Grinder and Richard Bandler and their brilliant student Robert Dilts, and shows how this direct, powerful, and elegant means for personal growth has developed and changed over its more than forty years of evolution. When a clinical psychologist, Jonathan Rice, started using these potent NLP tools in his own practice, and taught his methods to Carl Buchheit, this started a new branch of both psychology and NLP. Transformational NLP incorporates material drawn from, or inspired by, the holographic model of the universe as explained by physicist David Bohm, the basic premises and implications of twentieth and twenty-first century quantum mechanics, Bert Hellinger's trans-generational, systemic constellation work, and the metaphysics of the perennial philosophy such as described by Aldous Huxley. It offers breakthrough insights and unique methods--neuro-linguistic and otherwise--that Buchheit has developed over the course of more than three decades, working with thousands of clients. Buchheit explains that the key to change is to have more "rapport with self" by understanding the positive intentions in our unconscious that motivated our thoughts and behavior in the past. He shows how it is possible to alter the meaning of the past so it leads to the future we desire, and he uses the principles of quantum physics to assist the client to manifest an alternative reality. He demonstrates that we can become free of our unconscious addiction to the patterns of loss and pain that were set in motion by the suffering of our ancestors, generations before we were born. Most importantly, he describes new approaches and methods that empower people to have more choice in their lives, and to achieve their dreams by becoming more and more of who they really are and who they want to be. This book will be of great interest to all students of NLP as well as to psychologists, social workers, mental health workers, teachers, historians, and philosophers. It will especially appeal to many people who are interested in personal transformation and gaining entirely new perspectives about understanding and changing our human experience.

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

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