Bustos J. Generative AI Application Integration Patterns...2024 PDF

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Bustos J. Generative AI Application Integration Patterns...2024 PDF

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Textbook in PDF format What you will learn Concepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAG Framework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentation Patterns for batch and real-time integration Code samples for metadata extraction, summarization, intent classification, question-answering with RAG, and more Ethical use: bias mitigation, data privacy, and monitoring Deployment and hosting options for GenAI models Who this book is for This book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in production. While all readers are welcome, those who benefit most include Developer engineers with foundational tech knowledge Software architects seeking best practices and design patterns Professionals using ML for data science, research, etc., who want a deeper understanding of Generative AI Technical product managers with a software development background This concise focus ensures practical, actionable insights for experienced professionals Table of Contents Introduction to Generative AI Design Patterns Identifying Generative AI Use Cases Designing Patterns for Interacting with Generative AI Generative AI Batch & Real-time Integration Patterns Integration Pattern: Batch Metadata Extraction Integration Pattern: Batch Summarization Integration Pattern: Real-Time Intent Classification Integration Pattern: Real-Time Retrieval Augmented Generation Operationalizing Generative AI Integration Patterns Embedding Responsible AI into your GenAI Applications