Hands-On Large Language Models: Language Understanding and Generation (Paperback or Softback)
Language: English
Published by O'Reilly Media 10/15/2024, 2024
- Softcover
- New
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
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Add to basketItem description from seller
Hands-On Large Language Models: Language Understanding and Generation.
Seller Inventory # BBS-9781098150969
- Title
- Hands-On Large Language Models: Language Understanding and Generation (Paperback or Softback)
- Author
- Alammar, Jay
- Publisher
- O'Reilly Media 10/15/2024
- Publication year
- 2024
- Condition
- New
- Book Type
- Book
- Binding
- Paperback or Softback
- Language
- English
- ISBN 10
- 1098150961
- ISBN 13
- 9781098150969
- Item weight
- 1.49 pounds
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 representation
- Build advanced LLM pipelines to cluster text documents and explore the topics they cover
- Build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers
- Explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation
- Gain 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
"Synopsis" may belong to another edition of this title.
About the Author
Maarten Grootendorst is a Senior Clinical Data Scientist at IKNL (Netherlands Comprehensive Cancer Organization). He holds master's degrees in organizational psychology, clinical psychology, and data science which he leverages to communicate complex Machine Learning concepts to a wide audience. With his popular blogs, he has reached millions of readers by explaining the fundamentals of Artificial Intelligence--often from a psychological point of view. He is the author and maintainer of several open-source packages that rely on the strength of Large Language Models, such as BERTopic, PolyFuzz, and KeyBERT. His packages are downloaded millions of times and used by data professionals and organizations worldwide.
"About the title" may belong to another edition of this title.
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