Key Features
Backed by the community and written by an NLP expert
Get an understanding of basic NLP problems and terminology
Solve real-world NLP problems with Flair with the help of practical hands-on exercises
Book 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 learn
Gain an understanding of core NLP terminology and concepts
Get to grips with the capabilities of the Flair NLP framework
Find out how to use Flair's state-of-the-art pre-built models
Build custom sequence labeling models, embeddings, and classifiers
Learn about a novel text classification technique called TARS
Discover how to build applications with Flair and how to deploy them to production