Natural language processing using (414 résultats)

Supertagging: Using Complex Lexical Descriptions in Natural Language Processing
Martha Palmer; Srinivas Bangalore; Vijay K. Shanker; Fei Xia; Aravind K. Joshi
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Langue : anglais
Edité par Mercury Learning and Information 3/24/2022, 2022
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Paperback. Etat : Good. Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you. The next stage is to learn to build a chatbot using the API.ai platform and define its intents and entities. During this example, you will learn to enable communication with your bot and also take a look at key points of its integration and deployment.The final chapter of Building Chatbots with Python teaches you how to build, train, and deploy your very own chatbot. Using open source libraries and machine learning techniques you will learnto predict conditions for your bot and develop a conversational agent as a web application. Finally you will deploy your chatbot on your own server with AWS. What You Will LearnGain the basics of natural language processing using Python Collect data and train your data for the chatbotBuild your chatbot from scratch as a web appIntegrate your chatbots with Facebook, Slack, and TelegramDeploy chatbots on your own serverWho This Book Is ForIntermediate Python developers who have no idea about chatbots. Developers with basic Python programming knowledge can also take advantage of the book.…

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Paperback. Etat : Good. Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you. The next stage is to learn to build a chatbot using the API.ai platform and define its intents and entities. During this example, you will learn to enable communication with your bot and also take a look at key points of its integration and deployment.The final chapter of Building Chatbots with Python teaches you how to build, train, and deploy your very own chatbot. Using open source libraries and machine learning techniques you will learnto predict conditions for your bot and develop a conversational agent as a web application. Finally you will deploy your chatbot on your own server with AWS. What You Will LearnGain the basics of natural language processing using Python Collect data and train your data for the chatbotBuild your chatbot from scratch as a web appIntegrate your chatbots with Facebook, Slack, and TelegramDeploy chatbots on your own serverWho This Book Is ForIntermediate Python developers who have no idea about chatbots. Developers with basic Python programming knowledge can also take advantage of the book.…

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Paperback. Etat : Very Good. Natural Language Processing Crash Course for BeginnersArtificial Intelligence (AI) isn't the latest fad The reason is AI has been around since 1956, and its relevance is evident in every field today. Artificial Intelligence incorporates human intelligence into machines. Machine Learning (ML), a branch of AI, enables machines to learn by themselves. Deep Learning (DL), a subfield of Machine Learning, uses algorithms that are inspired by the functioning of the human brain. Natural Language Processing (NLP) combines computational linguistics and Artificial Intelligence, enabling computers and humans to communicate seamlessly. And NLP is immensely powerful and impactful as every business is looking to integrate it into their day to day dealings.How Is This Book Different?This book by AI Publishing is carefully crafted, giving equal importance to the theoretical concepts as well as the practical aspects of natural language processing. In each chapter of the second half of the book, the theoretical concepts of different types of deep learning and NLP techniques have been covered in-depth, followed by practical examples. You will learn how to apply different NLP techniques using the TensorFlow and Keras libraries for Python. Each chapter contains exercises that are designed to evaluate your understanding of the concepts covered in that chapter. Also, in the Resources section of each chapter, you can access the Python notebook. The author has also compiled a list of hands-on NLP projects and competitions that you can try on your own. The main benefit of purchasing this book is you get immediate access to all the extra learning material presented with this book--Python codes, exercises, PDFs, and references--on the publisher's website without having to spend an extra cent. You can download the datasets used in this book at runtime, or you can access them in the Resources/Datasets folder.The author holds your hand through everything. He provides you a step by step explanation of the installation of the software needed to implement the various NLP techniques in this book. You can start experimenting with the practical aspects of NLP right from the beginning.Even if you are new to Python, you'll find the ultra-short course on Python programming language in the second chapter immensely helpful. You get all the codes and datasets with this book. So, if you have access to a computer with the internet, you can get started. The topics covered include: What is Natural Language Processing?Environment Setup and Python Crash CourseIntroduction to Deep LearningText Cleaning and ManipulationCommon NLP TasksImporting Text Data from Various SourcesWord Embeddings: Converting Words to NumbersIMDB Movies Sentimental AnalysisHam and Spam Message ClassificationText Summarization and Topic ModelingText Classification with Deep LearningText Translation Using Seq2Seq ModelState of the Art NLP with BERT TransformersHands-on NLP Projects/Articles for PracticeExercise SolutionsClick the BUY button and download the book now to start your Natural Language Processing journey. …

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