You're reading from Generative AI with Amazon Bedrock Build, scale, and secure generative AI applications using Amazon Bedrock

Product type Paperback

Published in Jul 2024

Publisher Packt

ISBN-13 9781803247281

Length 384 pages

Edition 1st Edition

Tools

AWS

Concepts

Artificial Intelligence

Authors (2):

Shikhar Kwatra

Bunny Kaushik

View More author details

Table of Contents (18) Chapters

Preface

1. Part 1: Amazon Bedrock Foundations FREE CHAPTER

2. Chapter 1: Exploring Amazon Bedrock

3. Chapter 2: Accessing and Utilizing Models in Amazon Bedrock

4. Chapter 3: Engineering Prompts for Effective Model Usage

5. Chapter 4: Customizing Models for Enhanced Performance

6. Chapter 5: Harnessing the Power of RAG

7. Part 2: Amazon Bedrock Architecture Patterns

8. Chapter 6: Generating and Summarizing Text with Amazon Bedrock

9. Chapter 7: Building Question Answering Systems and Conversational Interfaces

10. Chapter 8: Extracting Entities and Generating Code with Amazon Bedrock

11. Chapter 9: Generating and Transforming Images Using Amazon Bedrock

12. Chapter 10: Developing Intelligent Agents with Amazon Bedrock

13. Part 3: Model Management and Security Considerations

14. Chapter 11: Evaluating and Monitoring Models with Amazon Bedrock

15. Chapter 12: Ensuring Security and Privacy in Amazon Bedrock

16. Index

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To get the most out of this book

You will need to have basic knowledge of Python and AWS. Having a basic understanding of Generative AI and the ML workflow would be an advantage.

Software/hardware covered in the book	Operating system requirements
Python	Linux-based OS
Amazon Web Services
Jupyter-based notebooks, such as Amazon SageMaker

This book requires you to have access to an Amazon Web Services (AWS) account. If you don’t have it already, you can go to https://aws.amazon.com/getting-started/ and create an AWS account.

Secondly, you will need to install and configure AWS Command-Line Interface (CLI) (https://aws.amazon.com/cli/) after you create an account, which will be needed to access Amazon Bedrock foundation models from your local machine.

Thirdly, since the majority of code cells that we will execute are based in Python, setting up an AWS Python SDK (Boto3) (https://docs.aws.amazon.com/bedrock/latest/APIReference/welcome.html) will be required. You can carry out the Python setup in the following ways: install it on your local machine, use AWS Cloud9, utilize AWS Lambda, or leverage Amazon SageMaker.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.