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Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4
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Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4
Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4
Nº de artículo: 49261621

Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and

87% of respondents would recommend this to a friend

Nº de artículo: 49261621

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What Stands Out

Comprehensive Coverage
This edition thoroughly covers deep learning architectures for NLP, offering detailed insights on architectures like GPT-3, ChatGPT, and GPT-4, making it ideal for both beginners and experienced practitioners.
Hands-On Approach
Offers practical exercises and real-world examples using Python and Hugging Face, empowering readers to build, train, and fine-tune models effectively, enhancing their practical understanding of NLP applications.
Updated Technologies
Incorporates the latest advancements in NLP technology, ensuring readers gain current knowledge on state-of-the-art models, preparing them for modern industry challenges and advanced computational techniques.

Detalles de producto

Shop Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 online at a best price in Ecuador. 1803247339
Publisher Packt Publishing
Publication date March 25, 2022
Edition 2nd ed.
Language English
Print length 602 pages
ISBN-10 1803247339
ISBN-13 978-1803247335
Item Weight 2.25 pounds (1.02 kg)
Dimensions 7.5 x 1.36 x 9.25 inches (19.1 x 3.5 x 23.5 cm)

Who Should Buy?

Suitable For
  • AI Enthusiasts

    Individuals keen on understanding deep learning and NLP will find this resource invaluable for hands-on learning.

  • Data Scientists

    Professionals who work with text data can benefit from practical knowledge of transformers in real-world applications.

  • Machine Learning Students

    Students pursuing machine learning courses can effectively apply theories through coding examples and projects presented in the book.

Not Suitable For
  • Beginner Programmers

    Individuals with no programming experience may struggle with the advanced concepts and coding implementations presented.

DESCRIPCIÓN DEL PRODUCTO

Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4

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Neural Networks Editorial Review

Transformers for Natural Language Processing, 2nd Edition by Denis Rothman is a comprehensive and well-written book that explains AI, NLP, and transformers. The author is an authority in the domain and gives a good superficial tutorial for beginners who want to enter the field and sound like an expert. The book offers detailed code examples that allow readers to get hands-on experience. As per the reviews, this book is highly recommended for breaking into NLP. There is praise for the author's simplicity combined with technical rigor. While most reviews are all praises, there is one critical review that suggests the book does not have actual content but is all hype. The reviewer suggests that the author might not understand transformers well, and the content on the book might be made up. Many reviews recommend publishers to offer more prominent fonts. This book is an essential read for beginners who want to enter the NLP field, and the code examples offer enough hands-on experience to get started.

Customer Reviews & Ratings

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ventajas

  • Comprehensive and well-written book on AI, NLP, and transformers.
  • The book offers detailed code examples that allow readers to get hands-on experience.
  • Simple and easy to understand language.
  • Recommended for beginners who want to enter the NLP field.

Contras

  • One critical review suggests that the book might not have actual content but is all hype.

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