Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects
Master the core techniques to develop and deploy several AI applications at scale
Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks
Purchase of the print or Kindle book includes a free PDF eBook
Description
The concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure.
Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock.
By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.
Who is this book for?
This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.
What you will learn
Explore the generative AI landscape and foundation models in Amazon Bedrock
Fine-tune generative models to improve their performance
Explore several architecture patterns for different business use cases
Gain insights into ethical AI practices, model governance, and risk mitigation strategies
Enhance your skills in employing agents to develop intelligence and orchestrate tasks
Monitor and understand metrics and Amazon Bedrock model response
Explore various industrial use cases and architectures to solve real-world business problems using RAG
Stay on top of architectural best practices and industry standards
If you're looking to dive into the world of generative AI without getting bogged down by infrastructure details, this book is a gem. Kwatra and Kaushik make it easy to understand how Amazon Bedrock works, covering everything from choosing the right models to real-world applications like RAG (Retrieval Augmented Generation) and intelligent agents. I particularly enjoyed the clear explanations and hands-on examples that help you get up and running quickly. It’s ideal for developers, data scientists, and AI enthusiasts eager to leverage Amazon’s powerful AI tools. Definitely worth the read if you’re ready to take your AI projects to the next level!
Amazon Verified review
S.KunduOct 01, 2024
5
The book "𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐰𝐢𝐭𝐡 𝐀𝐦𝐚𝐳𝐨𝐧 𝐁𝐞𝐝𝐫𝐨𝐜𝐤" will help you to gain a strong understanding of building and scaling generative AI applications with Amazon Bedrock, along with key architectural patterns and security best practices to help solve business challenges and drive innovation within your organization.Few highlights of the book are as below:The first section introduces Amazon Bedrock by exploring the Generative AI landscape and foundation models available on the platform. It offers guidelines for selecting the right model for various use cases and discusses additional generative AI capabilities.It then highlights various methods for accessing and utilizing Bedrock, including APIs, code snippets and integration with LangChain. It introduces PartyRock, Bedrock’s playground for building customized pipelines and chaining multiple models.The next part explores prompt engineering, offering techniques and best practices for crafting prompts to optimize the use of generative AI models. It equips readers with a solid understanding of how to create prompts that elicit desired outcomes.Additionally, the book provides a detailed guide on customizing foundation models for enhanced performance in domain-specific use cases. It covers data preparation, creating custom models and analyzing results, offering insights into best practices for successful model customization.Then the book dives into the Retrieval Augmented Generation (RAG) approach, explaining how external data sources can be integrated with language models to reduce hallucination. It covers the use of RAG with Amazon Bedrock and discusses alternative methods such as LangChain.Following this, the book explores text generation and summarization using Bedrock’s capabilities, with a focus on real-world use cases. Additionally, it addresses how to build question-answering systems and conversational interfaces, emphasizing prompt engineering techniques, conversation memory, embeddings and contextual awareness for creating intelligent and engaging chatbots.The next part delves into advanced applications of Amazon Bedrock, including entity extraction and code generation, providing practical strategies for implementation. It also covers image generation using Bedrock’s multimodal models and explores real-world applications, design patterns for multimodal systems and ethical safeguards.Finally, the book provides comprehensive coverage of evaluating and monitoring models using AWS tools, alongside a deep dive into the security and privacy measures in place, such as data encryption, access control and content filtering, ensuring responsible AI practices.
Amazon Verified review
CustomerSep 28, 2024
1
The book was priced more than double when I bought. Does not look like original.
Amazon Verified review
Devmallya KararAug 25, 2024
5
"Generative AI with Amazon Bedrock" is an outstanding resource for anyone looking to dive into the world of generative AI using Amazon's powerful Bedrock service. The book is well-structured, making complex topics accessible even for those who are new to the field. It covers everything from building and scaling AI applications to securing them effectively, offering practical examples and clear explanations. The authors do a great job of balancing theory with hands-on exercises, which makes the content both engaging and useful. If you're looking to enhance your AI skills or explore the capabilities of Amazon Bedrock, this book is a valuable addition to your library. Highly recommended for developers, data scientists, and tech leaders alike!
Amazon Verified review
Michael PrinceAug 24, 2024
5
Great level of detail into the GenAi landscape and powers of Bedrock.
Amazon Verified review
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About the authors
Shikhar Kwatra
Shikhar Kwatra
Shikhar Kwatra, a senior AI/ML solutions architect at Amazon Web Services, holds the distinction of being the world's Youngest Master Inventor with over 500 patents in AI/ML and IoT domains. He serves as a technical journal reviewer, book author, and educator. Shikhar earned his Master's in Electrical Engineering from Columbia University. With over a decade of experience spanning startups to large-scale enterprises, he specializes in architecting scalable, cost-efficient cloud environments and supports GSI partners in developing strategic industry solutions. Beyond his professional pursuits, Shikhar finds joy in playing the guitar, composing music, and practicing mindfulness.
Bunny Kaushik is an AWS solution architect and ML specialist who loves to build solutions and help customers innovate on the AWS platform. He is an Amazon SageMaker SME, generative AI hero, and ML thought leader within AWS. He has over 10 years of experience working as an ML specialist and managing projects across different teams and organizations. Outside of work, he enjoys swimming, playing volleyball, rock climbing, and exploring new places.
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