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Total Size:
29.5 MB
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9A39487B20ED4170D837E0420DD2D1E9DD1EECAB
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July 10, 2025, 12:16 p.m.
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(Last updated: July 10, 2025, 12:16 p.m.)
| File | Size |
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| ['Bhattacharjee A. A Practical Guide to Generative AI Using Amazon Bedrock...2025.pdf'] | 0 bytes |
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29.5 MB
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2025-07-10
| Uploaded by andryold1 | Size 29.5 MB | Health [ 29 /10 ] | Added 2025-07-10 |
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SOURCE: Bhattacharjee A. A Practical Guide to Generative AI Using Amazon Bedrock...2025
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COVER
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MEDIAINFO
Textbook in PDF format 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. Deep Learning architectures such as autoencoders, generative adversarial networks (GANs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), variational autoencoders (VAEs), attention mechanisms, and transformer-based models have made remarkable strides in the field of Generative Artificial Intelligence. These networks produce works that resemble those made by humans because they use neural networks to learn patterns and distributions within datasets. Generative AI applications cover areas ranging from content creation through data augmentation into image-to-image translation as well as language modeling. 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. Preface Introduction to Generative AI Generative AI with AWS Introduction to Amazon Bedrock Overview of Prompt Engineering and In-Context Learning Overview of Use Cases in This Book Overview of Retrieval-Augmented Generation (RAG) Overview of Amazon Bedrock Knowledge Bases Overview of Safeguard’s Practice Overview of Amazon Bedrock Agents Overview of Model Customization Overview of Model Evaluation Overview of Best Model Selection and Best Practices Overview of Security and Privacy of Amazon Bedrock Overview of GenAIOPS Overview of Prompt Management Overview of Prompt Flow Overview of Provisioned Throughput Overview of Image Capabilities Overview of Multimodal Capabilities Conclusion
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