May 2025
Intermediate to advanced
312 pages
4h 10m
Chinese
Overview
本作品已使用人工智能进行翻译。欢迎您提供反馈和意见：translation-feedback@oreilly.com
如今，许多公司正在迅速将生成式人工智能整合到他们的产品和服务中。但关于这项技术的影响和前景，存在许多炒作和误解。在这本书中，来自 AWS 的 Chris Fregly、Antje Barth 和 Shelbee Eigenbrode 帮助首席技术官、机器学习从业者、应用程序开发人员、业务分析师、数据工程师和数据科学家找到了使用这项令人兴奋的新技术的实用方法。
您将学习生成式人工智能项目的生命周期，包括用例定义、模型选择、模型微调、检索增强生成、从人类反馈中强化学习，以及模型量化、优化和部署。您还将探索不同类型的模型，包括大型语言模型 （LLMs） 和多模态模型，例如用于生成图像的 Stable Diffusion 和用于回答图像问题的 Flamingo/IDEFICS。
- 将生成式人工智能应用于您的业务用例
- 确定最适合您任务的生成式人工智能模型
- 执行 prompt 工程和上下文学习
- 使用低秩适应（LoRA）在您的数据集上微调生成式人工智能模型
- 通过强化学习从人类反馈（RLHF）中对生成式人工智能模型进行人类价值观对齐
- 通过检索增强生成（RAG）增强您的模型
- 探索 LangChain 和 React 等库，以开发代理和动作
- 使用Amazon Bedrock构建生成式AI应用程序
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