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Natural Language Processing with Flair. A practical guide to understanding and solving NLP problems with Flair Tadej Magajna

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Natural Language Processing with Flair. A practical guide to understanding and solving NLP problems with Flair Tadej Magajna - okladka książki

Natural Language Processing with Flair. A practical guide to understanding and solving NLP problems with Flair Tadej Magajna - okladka książki

Autor:
Tadej Magajna
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
200
Dostępne formaty:
     PDF
     ePub

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Prezent last minute w ebookpoint.pl
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.

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O autorze książki

Tadej Magajna is a former lead machine learning engineer, former data scientist, master of Computer Science and now a software engineer at Microsoft. He currently works in a team responsible for language model training and building language packs for keyboards. He started his career as a 15-year-old at a local media company as a web developer and progressed towards more complex engineering and machine learning problems. He tackled problems like NLP market research, public transport bus and train capacity forecasting and finally language model training at his current role. Today, he is based in his hometown Ljubljana, Slovenia.

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