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Ekaterine Kochmar

Getting Started with Natural Language Processing

Edition 1

Getting Started with Natural Language Processing

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Best.Nr.
978-1-6172-9676-5
Umfang
325 Seiten
Erscheint im
Februar 2021
Sprache
Englisch
Lieferzeit
nach Erscheinungstermin
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€ 38,84
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Getting Started with Natural Language Processing is a hands-on guide filled with everything you need to get started with NLP in a friendly, understandable tutorial. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away.

 

By following the numerous Python-based examples and real-world case studies, you’ll apply NLP to search applications, extracting meaning from text, sentiment analysis, user profiling, and more. When you’re done, you’ll have a solid grounding in NLP that will serve as a foundation for further learning.

 

Key Features

·   Extracting information from raw text

·   Named entity recognition

·   Automating summarization of key facts

·   Topic labeling

 

For beginners to NLP with basic Python skills.

 

 



Getting Started with Natural Language Processing is a hands-on guide filled with everything you need to get started with NLP in a friendly, understandable tutorial. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away.

 

By following the numerous Python-based examples and real-world case studies, you’ll apply NLP to search applications, extracting meaning from text, sentiment analysis, user profiling, and more. When you’re done, you’ll have a solid grounding in NLP that will serve as a foundation for further learning.

 

Key Features

·   Extracting information from raw text

·   Named entity recognition

·   Automating summarization of key facts

·   Topic labeling

 

For beginners to NLP with basic Python skills.

 

About the technology

Natural Language Processing is a set of data science techniques that enable machines to make sense of human text and speech. Advances in machine learning and deep learning have made NLP more efficient and reliable than ever, leading to a huge number of new tools and resources. From improving search applications to sentiment analysis, the possible applications of NLP are vast and growing.

 

Ekaterina Kochmar is an Affiliated Lecturer and a Senior Research Associate at the Natural Language and Information Processing group of the Department of Computer Science and Technology, University of Cambridge. She holds an MA degree in Computational Linguistics, an MPhil in Advanced Computer Science, and a PhD in Natural Language Processing.

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