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Build a Large Language Model (From Scratch)
90% of respondents would recommend this to a friend
MZN 4263
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This is an engaging book that covers each stage of the process, from planning and coding to training and fine-tuning.
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O que se Destaca
Detalhes do produto
| Publisher | Manning |
| Publication date | October 29, 2024 |
| Language | English |
| Print length | 368 pages |
| ISBN-10 | 1633437167 |
| ISBN-13 | 978-1633437166 |
| Item Weight | 1.35 pounds (610 grams) |
| Dimensions | 7.38 x 0.7 x 9.25 inches (18.7 x 1.8 x 23.5 cm) |
Quem Deverá Comprar?
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AI Enthusiasts
Perfect for those eager to deepen their understanding of AI and machine learning by building models from ground up.
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Developers
Essential for programmers looking to expand their skills in natural language processing and model creation techniques.
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Researchers
Ideal for academic professionals aiming to conduct experiments and showcase their findings using custom-built language models.
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Beginners
Might overwhelm new learners without prior knowledge in AI, as it requires understanding complex concepts and coding.
DESCRIÇÃO DO PRODUTO
Build a Large Language Model (From Scratch)
Perguntas e respostas do cliente
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Pergunta:
What prior knowledge do I need to get started?
Resposta: You need intermediate Python skills and some knowledge of machine learning. -
Pergunta:
Can I use this book on any laptop?
Resposta: Yes, the LLM you create will run on any modern laptop and can optionally utilize GPUs. -
Pergunta:
Does the book provide any additional resources?
Resposta: Yes, purchasing the print book includes a free eBook in PDF and ePub formats.
Expert Systems Editorial Review
**** The book "Build a Large Language Model From Scratch" has received an overwhelmingly positive reception from customers, particularly those with a background in machine learning or related fields. Many reviews highlight the book's structured approach to breaking down complex topics, making the intricate world of large language models (LLMs) accessible to readers without overwhelming them. Readers appreciate the step-by-step progression through the material, which allows them to incrementally build their understanding of LLMs and their underlying architectures. Specifically, the clarity in explaining concepts such as vanishing gradients and ReLU activations, coupled with practical examples and source code, has been noted as a strong point that enhances learning. The inclusion of an 80-page appendix further enriches the reader's experience by delving deeper into PyTorch and neural network principles. The book stands out for its commitment to practical learning, with many users praising its detailed, coherent explanations and the availability of working code samples that can be executed without hiccups. Many reviewers also appreciated the situation of code in relevant contexts—this integrated approach enables readers to visualize theoretical concepts alongside their practical applications, reinforcing their learning. Critics, however, have pointed out minor issues about needing a clean book for a more satisfying reading experience, which could be indicative of a desire for a digital option. Overall, this book is highly recommended for anyone looking to deepen their understanding of language models from the ground up, whether they are researchers or machine learning engineers looking to enhance their skills through hands-on experience. **
Avaliações e Classificações dos Clientes
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100%
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Prós
- Well-structured content that builds knowledge incrementally.
- Detailed explanations of complex concepts, including practical applications.
- Integration of working Python/PyTorch code that can be executed out of the box.
- Clear and coherent writing style with accompanying flow diagrams.
- Suitable as both a how-to guide and a reference book.
Contras
- Some readers indicate the desire for a more pristine book condition for reading.
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MZN 4263
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Recursos e benefícios
- Learn to build large language models (LLMs) from scratch.
- Step-by-step guidance from renowned author Sebastian Raschka.
- Hands-on approach covering planning, coding, training, and fine-tuning.
- Develop your own LLM that runs on an ordinary laptop.
- Includes a free eBook with the print purchase for easy access.
- Gain a deep understanding of LLMs and their customization methods.
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