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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) Język publikacji: angielski
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:
Bądź pierwszym, który oceni tę książkę
Stron:
238
Dostępne formaty:
     PDF
     ePub
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Do przechowalni

Mastering spaCy, Second Edition is your comprehensive guide to building sophisticated NLP applications using the spaCy ecosystem. This revised edition builds on the expertise of Duygu Altinok, a seasoned NLP engineer and spaCy contributor, and introduces new chapters by Déborah Mesquita, a data science educator and consultant known for making complex concepts accessible.
This edition embraces the latest advancements in NLP, featuring chapters on large language models with spacy-llm, transformer integration, and end-to-end workflow management with Weasel.
You’ll learn how to enhance NLP tasks using LLMs, streamline workflows using Weasel, and integrate spaCy with third-party libraries like Streamlit, FastAPI, and DVC. From training custom Named Entity Recognition (NER) pipelines to categorizing emotions in Reddit posts, this book covers advanced topics such as text classification and coreference resolution. Starting with the fundamentals—tokenization, NER, and dependency parsing—you’ll explore more advanced topics like creating custom components, training domain-specific models, and building scalable NLP workflows.
Through practical examples, clear explanations, tips, and tricks, this book will equip you to build robust NLP pipelines and seamlessly integrate them into web applications for 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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