This comprehensive guide gives you the knowledge and skills you need to excel in Generative AI. From understanding the fundamentals to mastering techniques, this book offers a step-by-step approach to leverage Amazon Bedrock to build, deploy, and secure Generative AI applications.
The book presents structured chapters and practical examples to delve into key concepts such as prompt engineering, retrieval-augmented generation, and model evaluation. You will gain profound insights into the Amazon Bedrock platform. The book covers setup, life cycle management, and integration with Amazon SageMaker. The book emphasizes real-world applications, and provides use cases and best practices across industries on topics such as text summarization, image generation, and conversational AI bots. The book tackles vital topics including data privacy, security, responsible AI practices, and guidance on navigating governance and monitoring challenges while ensuring adherence to ethical standards and regulations.
The book provides the tools and knowledge needed to excel in the rapidly evolving field of Generative AI. Whether you're a data scientist, AI engineer, or business professional, this book will empower you to harness the full potential of Generative AI and drive innovation in your organization.
What You Will Learn
- Understand the fundamentals of Generative AI and Amazon Bedrock
- Build Responsible Generative AI applications leveraging Amazon Bedrock
- Know techniques and best practices
- See real-world applications
- Integrate and manage platforms
- Handle securty and governance issues
- Evaluate and optimze models
- Gain future-ready insights
- Understand the project life cycle when building Generative AI Applications
Who This Book Is For
Data scientistys, AI/ML engineers and architects, software developers plus AI enthusiasts and studenta and educators, and leaders who want to evangelize within organizatios
Table of Contents:
Chapter 1: Introduction to Generative AI.- Chapter 2: Generative AI with AWS.- Chapter 3: Introduction to Amazon Bedrock.- Chapter 4: Overview of Prompt Engineering and In-Context Learning.- Chapter 5: Overview of Use Cases in this Book.- Chapter 6: Overview of Retrieval-Augmented Generation (RAG).- Chapter 7: Overview of Amazon Bedrock Knowledge Base.- Chapter 8: Overview of Safeguard's Practice.- Chapter 9: Overview of Amazon Bedrock Agents.- Chapter 10: Overview of Model Customization.- Chapter 11: Overview of Model Evaluation.- Chapter 12: Overview of Best Model Selection and Best Practices.- Chapter 13: Overview of Security and Privacy of Amazon Bedrock.- Chapter 14: Overview of GenAIOps.- Chapter 15: Overview of Prompt Management.- Chapter 16: Overview of Prompt Flow. – Chapter 17: Overview of Provisional Throughput. – Chapter 18: Overview of Image Capabilities. – Chapter 19: Overview of Multimodal Capabilities. – Chapter 20: Conclusion.
About the Author :
Avik Bhattacharjee is a distinguished AI/ML and data evangelist, speaker, and tech blogger with over a decade of experience at the forefront of cutting-edge technology. With a robust background in AI/ML development, Avik has led numerous projects across diverse domains, including healthcare and finance. His expertise lies in crafting resilient AI solutions that harness the latest advancements in generative AI and machine learning algorithms. Recognized as a thought leader in the AI community, Avik's passion for innovation and commitment to excellence shine through his work. Leveraging his comprehensive understanding of AI technologies and platforms such as Amazon Bedrock, Avik empowers professionals globally to unleash the full potential of AI for transformative impact. Avik Bhattacharjee previously served as a Global Partner Solution Architect at Amazon Web Services (AWS).
