Hands-On Large Language Models: Language Understanding and Generation
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You'll learn practical tools and concepts you need to use these capabilities today.
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What Stands Out
Product Details
| Publishers | O'Reilly Media |
| Date of publicization | September 20, 2024 |
| Prints | . |
| Language | English |
| Print length | 400 pages |
| ISBN-10 | 1098150961 |
| ISBN-13 | 978-1098150969 |
| Dimensions | 17.78 x 2.21 x 23.34 cm |
Who Should Buy?
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Data Scientists
Ideal for professionals looking to integrate language models into data-centric applications and enhance data interpretation capabilities.
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AI Developers
Supports developers aiming to create conversational agents or applications utilizing natural language processing and understanding.
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Researchers
Valuable to researchers exploring the latest advancements in language models and their applications in various fields.
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Beginners
Not suitable for those with no prior knowledge of machine learning or natural language processing concepts.
Product Description
Hands-On Large Language Models: Language Understanding and Generation
Customer Questions & Answers
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Question:
What skills will I gain from this book?
Answer: You will learn practical tools for using pretrained language models and techniques for building semantic search systems. -
Question:
Is prior knowledge of AI necessary to understand this book?
Answer: No, the book is designed to be accessible and educational for readers at various levels of expertise in AI. -
Question:
What type of applications can I expect to build after reading this book?
Answer: You can build applications like automated copywriting tools, advanced search systems, and document clustering pipelines.
İngilizce Baskı Jay Alammar Editorial Review
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Pros
- Comprehensive coverage of topics
- Engaging writing style
- Practical examples provided
- User-friendly for beginners
- Up-to-date information
Cons
- Some chapters may be too detailed for casual readers.
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Features & Benefits
- Explore the cutting-edge of AI language capabilities.
- Learn to use pretrained language models for various applications.
- Build advanced pipelines for document clustering and topic exploration.
- Create semantic search engines that surpass traditional keyword searching.
- Master generative models through effective prompt engineering and fine-tuning.
- Understand the architecture of Transformer models for improved text generation.
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