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Generative AI on AWS (Early Release) - BaDshaH - 08-16-2023
![[Image: 520ce450ca51404dee3928a336608d24.jpg]](https://i122.fastpic.org/big/2023/0816/24/520ce450ca51404dee3928a336608d24.jpg)
Generative AI on AWS (Early Release)
English | 2023 | ISBN : 9781098159214 | 151 pages | Epub | 5 MB
Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. In this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, machine learning practitioners, business analysts, data engineers, and data scientists find a practical way to use this exciting new technology.
You'll learn the generative AI project lifecycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation (RAG), reinforcement learning from human feedback (RLHF), model quantization, optimization, and deployment. You'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and video. You'll also be able to make better-informed decisions for your company regarding generative AI and learn how to build working prototypes quickly. While the focus is on AWS, this book is a great resource for learning generative AI fundamentals and applying these models to real-world applications.
Apply generative AI to your business use cases
Determine which generative AI models to use based on the task
Perform prompt engineering and in-context learning
Fine-tune generative AI models on your datasets
Align generative AI models to human values with reinforcement learning from human feedback
Use techniques like retrieval-augmented generation to augment your model
Explore libraries such as LangChain and React to develop agents and actions
Learn about multimodal models such as Stable Diffusion for image and video generation
Get hands-on with Amazon Bedrock, the AWS generative AI managed service
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