Natural Language Processing with Flair

This book PDF is perfect for those who love Computers genre, written by Tadej Magajna and published by Packt Publishing Ltd which was released on 29 April 2022 with total hardcover pages 200. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Natural Language Processing with Flair books below.

Natural Language Processing with Flair
Author : Tadej Magajna
File Size : 44,8 Mb
Publisher : Packt Publishing Ltd
Language : English
Release Date : 29 April 2022
ISBN : 9781801072236
Pages : 200 pages
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Natural Language Processing with Flair by Tadej Magajna Book PDF Summary

Learn how to solve practical NLP problems with the Flair Python framework, train sequence labeling models, work with text classifiers and word embeddings, and much more through hands-on practical exercises Key FeaturesBacked by the community and written by an NLP expertGet an understanding of basic NLP problems and terminologySolve real-world NLP problems with Flair with the help of practical hands-on exercisesBook Description Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings. Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot learning through a novel text classification technique TARS. Finally, you will solve several real-world NLP problems through hands-on exercises, as well as learn how to deploy Flair models to production. By the end of this Flair book, you'll have developed a thorough understanding of typical NLP problems and you'll be able to solve them with Flair. What you will learnGain an understanding of core NLP terminology and conceptsGet to grips with the capabilities of the Flair NLP frameworkFind out how to use Flair's state-of-the-art pre-built modelsBuild custom sequence labeling models, embeddings, and classifiersLearn about a novel text classification technique called TARSDiscover how to build applications with Flair and how to deploy them to productionWho this book is for This Flair NLP book is for anyone who wants to learn about NLP through one of the most beginner-friendly, yet powerful Python NLP libraries out there. Software engineering students, developers, data scientists, and anyone who is transitioning into NLP and is interested in learning about practical approaches to solving problems with Flair will find this book useful. The book, however, is not recommended for readers aiming to get an in-depth theoretical understanding of the mathematics behind NLP. Beginner-level knowledge of Python programming is required to get the most out of this book.

Natural Language Processing with Flair

Learn how to solve practical NLP problems with the Flair Python framework, train sequence labeling models, work with text classifiers and word embeddings, and much more through hands-on practical exercises Key FeaturesBacked by the community and written by an NLP expertGet an understanding of basic NLP problems and terminologySolve real-world

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Natural Language Processing with Python and spaCy

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

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Natural Language Processing Fundamentals

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

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Applied Natural Language Processing in the Enterprise

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

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Getting started with Deep Learning for Natural Language Processing

Learn how to redesign NLP applications from scratch. KEY FEATURESÊÊ ¥ Get familiar with the basics of any Machine Learning or Deep Learning application. ¥ Understand how does preprocessing work in NLP pipeline. ¥ Use simple PyTorch snippets to create basic building blocks of the network commonly used inÊ NLP.Ê ¥ Learn how to

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Linguistic Fundamentals for Natural Language Processing

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

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Handbook of Natural Language Processing

The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater

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Natural Language Processing

Covers all aspects of the area of linguistic analysis and the computational systems that have been developed to perform the language analysis. The book is primarily meant for post graduate and undergraduate technical courses.

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