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90078875
Hands-On Large Language Models: Language Understanding and Generation
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Item #:
90078875
SAR 194
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What Stands Out
Comprehensive Techniques
Offers in-depth exploration of language understanding and generation techniques, equipping readers with practical skills and theoretical knowledge applicable in various AI-driven scenarios.
Hands-on Approach
Emphasizes experiential learning through practical examples and exercises, enhancing reader engagement and understanding of complex concepts in large language models.
Real-world Applications
Discusses the application of large language models in diverse industries, helping readers visualize and implement AI solutions that address real-life challenges effectively.
Product Details
- AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. Through this book's visually educational nature, readers will learn practical tools and concepts they need to use these capabilities today. You'll understand how to use pretrained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you: Understand the architecture of Transformer language models that excel at text generation and representationBuild advanced LLM pipelines to cluster text documents and explore the topics they coverBuild semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankersExplore how generative models can be used, from prompt engineering all the way to retrieval-augmented generationGain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context learning
| Publisher | O'Reilly Media |
| Publication date | October 15, 2024 |
| Edition | 1st |
| Language | English |
| Print length | 425 pages |
| ISBN-10 | 1098150961 |
| ISBN-13 | 978-1098150969 |
| Item Weight | 1.63 pounds (740 grams) |
| Dimensions | 7 x 0.87 x 9.19 inches (17.8 x 2.2 x 23.3 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for individuals seeking practical knowledge in large language models for data science applications and career advancement.
-
AI Researchers
Provides in-depth understanding and hands-on experience for researchers focusing on natural language processing and model development.
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Educators and Trainers
Useful resource for educators who want to incorporate large language models into teaching curricula on AI and NLP.
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Beginners in AI
Not suitable for those unfamiliar with basic concepts of artificial intelligence and machine learning methodologies.
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Natural Language Processing Editorial Review
Hands-On Large Language Models: Language Understanding and Generation is an insightful resource published by O'Reilly Media, set to release on October 15, 2024. This first edition spans 425 pages and delves into the intricacies of language models, offering a comprehensive guide for both beginners and seasoned researchers. The book is written in English and is designed to be user-friendly, enhancing readers' understanding of language generation and comprehension capabilities. It provides practical examples and applications, making complex concepts accessible. With its detailed design, it appeals to programmers and data scientists eager to explore the latest advancements in AI language models.
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Pros
- In-depth exploration of language models
- User-friendly practical examples provided
- Comprehensive coverage of key concepts
- Ideal for both beginners and experts
- Well-structured and easy to navigate
Cons
- May be dense for casual readers
Product Price History
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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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