Genai On Aws
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GenAI on AWS
Author: Olivier Bergeret
language: en
Publisher: John Wiley & Sons
Release Date: 2025-03-19
The definitive guide to leveraging AWS for generative AI GenAI on AWS: A Practical Approach to Building Generative AI Applications on AWS is an essential guide for anyone looking to dive into the world of generative AI with the power of Amazon Web Services (AWS). Crafted by a team of experienced cloud and software engineers, this book offers a direct path to developing innovative AI applications. It lays down a hands-on roadmap filled with actionable strategies, enabling you to write secure, efficient, and reliable generative AI applications utilizing the latest AI capabilities on AWS. This comprehensive guide starts with the basics, making it accessible to both novices and seasoned professionals. You'll explore the history of artificial intelligence, understand the fundamentals of machine learning, and get acquainted with deep learning concepts. It also demonstrates how to harness AWS's extensive suite of generative AI tools effectively. Through practical examples and detailed explanations, the book empowers you to bring your generative AI projects to life on the AWS platform. In the book, you'll: Gain invaluable insights from practicing cloud and software engineers on developing cutting-edge generative AI applications using AWS Discover beginner-friendly introductions to AI and machine learning, coupled with advanced techniques for leveraging AWS's AI tools Learn from a resource that's ideal for a broad audience, from technical professionals like cloud engineers and software developers to non-technical business leaders looking to innovate with AI Whether you're a cloud engineer, software developer, business leader, or simply an AI enthusiast, Gen AI on AWS is your gateway to mastering generative AI development on AWS. Seize this opportunity for an enduring competitive advantage in the rapidly evolving field of AI. Embark on your journey to building practical, impactful AI applications by grabbing a copy today.
AWS DevOps for GenAI Automating and Scaling AI Solutions
" In "AWS DevOps for GenAI: Automating and Scaling AI Solutions," explore the transformative synergy between DevOps practices and Generative AI (GenAI) within the AWS ecosystem. This comprehensive guide delves into the critical role of AWS DevOps tools in deploying and scaling GenAI applications efficiently. Learn how to set up a robust AWS environment, automate infrastructure with CloudFormation, streamline CI/CD processes with CodeDeploy, and implement comprehensive monitoring with CloudWatch. Integrate AWS SageMaker for end-to-end machine learning workflows while ensuring robust security and compliance. Discover strategies for optimizing performance and managing costs effectively. Through real-world case studies in healthcare, finance, and e-commerce, gain insights into successful implementations and best practices. Stay ahead with future trends and innovations, preparing for the next generation of AI solutions. Whether you're a developer, data scientist, or IT professional, this book equips you with the knowledge and tools to harness the full potential of AWS DevOps for GenAI. ... "
Generative AI on AWS
Author: Chris Fregly
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2023-11-13
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. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock