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Generative AI Application Integration Patterns
Generative AI Application Integration Patterns

Generative AI Application Integration Patterns: Integrate large language models into your applications

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Profile Icon Juan Pablo Bustos Profile Icon Luis Lopez Soria
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R$80 R$222.99
eBook Sep 2024 218 pages 1st Edition
eBook
R$80 R$222.99
Paperback
R$278.99
Subscription
Free Trial
Renews at R$50p/m
Arrow left icon
Profile Icon Juan Pablo Bustos Profile Icon Luis Lopez Soria
Arrow right icon
R$80 R$222.99
eBook Sep 2024 218 pages 1st Edition
eBook
R$80 R$222.99
Paperback
R$278.99
Subscription
Free Trial
Renews at R$50p/m
eBook
R$80 R$222.99
Paperback
R$278.99
Subscription
Free Trial
Renews at R$50p/m

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Generative AI Application Integration Patterns

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Key benefits

  • Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps
  • Interact with GenAI models to tailor model behavior to minimize hallucinations
  • Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications

Description

Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI. With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns. We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought. Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns.

Who is this book 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

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 05, 2024
Length: 218 pages
Edition : 1st
Language : English
ISBN-13 : 9781835887615
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Product Details

Publication date : Sep 05, 2024
Length: 218 pages
Edition : 1st
Language : English
ISBN-13 : 9781835887615
Category :
Languages :
Tools :

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Frequently bought together


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Table of Contents

12 Chapters
Introduction to Generative AI Patterns Chevron down icon Chevron up icon
Identifying Generative AI Use Cases Chevron down icon Chevron up icon
Designing Patterns for Interacting with Generative AI Chevron down icon Chevron up icon
Generative AI Batch and Real-Time Integration Patterns Chevron down icon Chevron up icon
Integration Pattern: Batch Metadata Extraction Chevron down icon Chevron up icon
Integration Pattern: Batch Summarization Chevron down icon Chevron up icon
Integration Pattern: Real-Time Intent Classification Chevron down icon Chevron up icon
Integration Pattern: Real-Time Retrieval Augmented Generation Chevron down icon Chevron up icon
Operationalizing Generative AI Integration Patterns Chevron down icon Chevron up icon
Embedding Responsible AI into Your GenAI Applications Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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