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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
UYU 4256
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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
| 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?
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AI Enthusiasts
Individuals keen on understanding deep learning and NLP will find this resource invaluable for hands-on learning.
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Data Scientists
Professionals who work with text data can benefit from practical knowledge of transformers in real-world applications.
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Machine Learning Students
Students pursuing machine learning courses can effectively apply theories through coding examples and projects presented in the book.
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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.
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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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