Generative AI Application Integration Patterns. (Record no. 15224)
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| control field | 20250710181507.0 |
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| 024 80 - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 9781835887615 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | PACKT |
| Transcribing agency | PACKT |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | en |
| 044 ## - COUNTRY OF PUBLISHING/PRODUCING ENTITY CODE | |
| MARC country code | GB |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Juan Pablo Bustos |
| Relator term | author. |
| 245 00 - TITLE STATEMENT | |
| Title | Generative AI Application Integration Patterns. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | GB: |
| Name of publisher, distributor, etc. | Packt, |
| Date of publication, distribution, etc. | 2024-09-05. |
| 263 ## - PROJECTED PUBLICATION DATE | |
| Projected publication date | 2024-09-05 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | GB: |
| Name of producer, publisher, distributor, manufacturer | Packt, |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 218. |
| 377 ## - ASSOCIATED LANGUAGE | |
| Language code | en |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | <p><b>Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations.</b></p><h4>Key Features</h4><ul><li>Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps</li><li>Interact with GenAI models to tailor model behavior to minimize hallucinations</li><li>Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications</li></ul><h4>Book Description</h4>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.<br/>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.<br/>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.<br/>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.<h4>What you will learn</h4><ul><li>Concepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAG</li><li>Framework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentation</li><li>Patterns for batch and real-time integration</li><li>Code samples for metadata extraction, summarization, intent classification, question-answering with RAG, and more</li><li>Ethical use: bias mitigation, data privacy, and monitoring</li><li>Deployment and hosting options for GenAI models</li></ul><h4>Who this book is for</h4>This book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in product_backupion. While all readers are welcome, those who benefit most include:<br/>Developer engineers with foundational tech knowledge<br/>Software architects seeking best practices and design patterns<br/>Professionals using ML for data science, research, etc., who want a deeper understanding of Generative AI<br/>Technical product_backup managers with a software development background<br/>This concise focus ensures practical, actionable insights for experienced professionals. |
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| System details note | Data in extended ASCII character set. |
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| System details note | Mode of access: Internet. |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Luis Lopez Soria |
| Relator term | author. |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Dr. Ali Arsanjani |
| Relator term | author. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | PACKT |
| 773 0# - HOST ITEM ENTRY | |
| Title | Generative AI Application Integration Patterns |
| Place, publisher, and date of publication | GB,Packt,2024-09-05 |
| Physical description | 218 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://learning.packt.com/product/477465">https://learning.packt.com/product/477465</a> |
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