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

Author: Joseph O'Connor
Publisher: Red Wheel/Weiser
ISBN: 1590035186
Category : Psychology
Languages : en
Pages : 306

View

Book Description
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.

Author: Sowmya Vajjala
Publisher: O'Reilly Media
ISBN: 149205402X
Category : Computers
Languages : en
Pages : 455

View

Book Description
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

Author: Neil Shah
Publisher: Icon Books Ltd
ISBN: 184831325X
Category : Self-Help
Languages : en
Pages : 180

View

Book Description
An INTRODUCING PRACTICAL GUIDE to the therapy designed to help people have better, fuller and richer lives – as well as work far more effectively. By focusing on how we communicate – the words we use as well as non-verbal communication such as body language – NLP seeks to change our mental habits into those of more successful people. Whether you're a salesperson needing to close more deals, a teacher who would like to get through to your pupils more quickly, or someone who needs to negotiate between parties – this INTRODUCING PRACTICAL GUIDE is for you.

Author: Jose Manuel Gomez-Perez
Publisher: Springer
ISBN: 9783030448325
Category : Computers
Languages : en
Pages : 268

View

Book Description
This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs. To this end, it first introduces the main building blocks and then describes how they can be integrated to support the effective implementation of real-world NLP applications. To illustrate the ideas described, the book also includes a comprehensive set of experiments and exercises involving different algorithms over a selection of domains and corpora in various NLP tasks. Throughout, the authors show how to leverage complementary representations stemming from the analysis of unstructured text corpora as well as the entities and relations described explicitly in a knowledge graph, how to integrate such representations, and how to use the resulting features to effectively solve NLP tasks in a range of domains. In addition, the book offers access to executable code with examples, exercises and real-world applications in key domains, like disinformation analysis and machine reading comprehension of scientific literature. All the examples and exercises proposed in the book are available as executable Jupyter notebooks in a GitHub repository. They are all ready to be run on Google Colaboratory or, if preferred, in a local environment. A valuable resource for anyone interested in the interplay between neural and knowledge-based approaches to NLP, this book is a useful guide for readers with a background in structured knowledge representations as well as those whose main approach to AI is fundamentally based on logic. Further, it will appeal to those whose main background is in the areas of machine and deep learning who are looking for ways to leverage structured knowledge bases to optimize results along the NLP downstream.

Author: Neil Shah
Publisher: Icon Books Ltd
ISBN: 1848319533
Category : Self-Help
Languages : en
Pages : 158

View

Book Description
Neurolinguistic programming (NLP) involves a range of psychological techniques that help you to 'reprogram' your brain – replacing the negative attitudes that hold you back with positive thought patterns that will enable you to be more effective, confident and successful. In just under 20 simple steps, Neil Shah shows you how to use NLP to develop new habits of behaviour and thought that will help you succeed in all areas of life, from influencing others and understanding how they influence you, to achieving your goals, to managing stress.

Author: Rajesh Arumugam
Publisher: Packt Publishing Ltd
ISBN: 1789135915
Category : Computers
Languages : en
Pages : 307

View

Book Description
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.

Author: Byron Lewis
Publisher: Crown House Publishing
ISBN: 184590818X
Category : Psychology
Languages : en
Pages : 181

View

Book Description
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.

Author: Bhargav Srinivasa-Desikan
Publisher: Packt Publishing Ltd
ISBN: 1788837037
Category : Computers
Languages : en
Pages : 298

View

Book Description
Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you!

Author: Catherine Stott
Publisher: Harriman House Limited
ISBN: 0857195042
Category : Self-Help
Languages : en
Pages : 392

View

Book Description
Trading is a minefield of psychological and emotional challenges. Hypnotherapy and neuro-linguistic programming (NLP) techniques are commonly used by psychotherapists to help traders defeat these challenges and become more profitable. Now, for the first time, these approaches are made available to all in HypnoTrading - a brand new step-by-step practical guide on how to use the latest psychotherapeutic approaches in the trading environment. HypnoTrading teaches a number of self-help solutions to make your mindset more positive, control your emotions and enhance your ability to deal with the common psychological issues traders face. You will discover the power of hypnosis and how to use self-hypnosis with NLP and Havening, a cutting-edge psycho-sensory technique, to identify and master the issues that inhibit your trading performance. With these methods, you will make better trading decisions, perform in a more calm and consistent manner, and improve your trading results. A wide range of practical techniques and activities are provided throughout. These have been designed specifically to combat the psychological challenges faced by traders. Once you are accustomed to using these techniques, you will have your own toolkit that you can use as often as required to help you change your mindset and improve your psychological approach to trading. You will be amazed at the impact a positive mindset, freedom from stress, anxiety and fear, and an ability to move on from losing trades will have on your trading results. HypnoTrading is your guide to making these changes.

Author: Yuli Vasiliev
Publisher: No Starch Press
ISBN: 171850053X
Category : Computers
Languages : en
Pages : 217

View

Book Description
An introduction to natural language processing with Python using spaCy, a leading Python natural language processing library. Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You'll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You'll even learn how to transform statements into questions to keep a conversation going. You'll also learn how to: • Work with word vectors to mathematically find words with similar meanings (Chapter 5) • Identify patterns within data using spaCy's built-in displaCy visualizer (Chapter 7) • Automatically extract keywords from user input and store them in a relational database (Chapter 9) • Deploy a chatbot app to interact with users over the internet (Chapter 11) "Try This" sections in each chapter encourage you to practice what you've learned by expanding the book's example scripts to handle a wider range of inputs, add error handling, and build professional-quality applications. By the end of the book, you'll be creating your own NLP applications with Python and spaCy.