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Mastering spaCy. Build structured NLP solutions with custom components and models powered by spacy-llm - Second Edition Déborah Mesquita, Duygu Altinok

(ebook) (audiobook) (audiobook) Książka w języku 1
Mastering spaCy. Build structured NLP solutions with custom components and models powered by spacy-llm - Second Edition Déborah Mesquita, Duygu Altinok - okladka książki

Mastering spaCy. Build structured NLP solutions with custom components and models powered by spacy-llm - Second Edition Déborah Mesquita, Duygu Altinok - okladka książki

Mastering spaCy. Build structured NLP solutions with custom components and models powered by spacy-llm - Second Edition Déborah Mesquita, Duygu Altinok - audiobook MP3

Mastering spaCy. Build structured NLP solutions with custom components and models powered by spacy-llm - Second Edition Déborah Mesquita, Duygu Altinok - audiobook CD

Autorzy:
Déborah Mesquita, Duygu Altinok
Ocena:
Stron:
238
Mastering spaCy, Second Edition is your comprehensive guide to building sophisticated NLP applications using the spaCy ecosystem. This revised edition embraces the latest advancements in NLP, featuring new chapters on Large Language Models with spaCy-LLM, transformers integration, and end-to-end workflow management with Weasel.
With this new edition you’ll learn to enhance NLP tasks using LLMs with spaCy-llm, manage end-to-end workflows using Weasel and integrating spaCy with third-party libraries like Streamlit, FastAPI, and DVC. From training custom named entity recognition (NER) pipelines to categorizing emotions in Reddit posts, readers will explore advanced topics like text classification and coreference resolution. This book takes you on a journey through spaCy’s capabilities, starting with the fundamentals of NLP, such as tokenization, named entity recognition, and dependency parsing. As you progress, you’ll delve into advanced topics like creating custom components, training domain-specific models, and building scalable NLP workflows.
By end of the book, through practical examples, clear explanations, tips and tricks you will be empowered to build robust NLP pipelines and integrate them with web applications to build end-to-end solutions.

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O autorze książki

Duygu Altinok is a senior NLP engineer with 12 years of experience in almost all areas of NLP including search engine technology, speech recognition, text analytics, and conversational AI. She authored several publications in the NLP area at conferences such as LREC and CLNLP. She also enjoys working on open-source projects and is a contributor to the spaCy library. Duygu earned her undergraduate degree in Computer Engineering from METU, Ankara in 2010 and later earned her Master's degree in Mathematics from Bilkent University, Ankara in 2012. She is currently a senior engineer at German Autolabs with a focus on conversational AI for voice assistants. Originally from Istanbul, Duygu currently resides in Berlin, DE with her cute dog Adele.

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