Building AI Intensive Python Applications. (Record no. 16062)
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control field | 20250710182907.0 |
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Standard number or code | 9781836207245 |
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Original cataloging agency | PACKT |
Transcribing agency | PACKT |
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Language code of text/sound track or separate title | en |
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MARC country code | GB |
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Personal name | Rachelle Palmer |
Relator term | author. |
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Title | Building AI Intensive Python Applications. |
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Place of publication, distribution, etc. | GB: |
Name of publisher, distributor, etc. | Packt, |
Date of publication, distribution, etc. | 2024-09-06. |
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Projected publication date | 2024-09-06 |
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Place of production, publication, distribution, manufacture | GB: |
Name of producer, publisher, distributor, manufacturer | Packt, |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 298. |
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Language code | en |
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Summary, etc. | <p><b>Master retrieval-augmented generation architecture and fine-tune your AI stack, along with discovering real-world use cases and best practices to create powerful AI apps</b></p><h4>Key Features</h4><ul><li>Get to grips with the fundamentals of LLMs, vector databases, and Python frameworks</li><li>Implement effective retrieval-augmented generation strategies with MongoDB Atlas</li><li>Optimize AI models for performance and accuracy with model compression and deployment optimization</li><li>Purchase of the print or Kindle book includes a free PDF eBook</li></ul><h4>Book Description</h4>The era of generative AI is upon us, and this book serves as a roadmap to harness its full potential. With its help, you'll learn the core components of the AI stack: large language models (LLMs), vector databases, and Python frameworks, and see how these technologies work together to create intelligent applications. The chapters will help you discover best practices for data preparation, model selection, and fine-tuning, and teach you advanced techniques such as retrieval-augmented generation (RAG) to overcome common challenges, such as hallucinations and data leakage. You'll get a solid understanding of vector databases, implement effective vector search strategies, refine models for accuracy, and optimize performance to achieve impactful results. You'll also identify and address AI failures to ensure your applications deliver reliable and valuable results. By evaluating and improving the output of LLMs, you'll be able to enhance their performance and relevance. By the end of this book, you'll be well-equipped to build sophisticated AI applications that deliver real-world value.<h4>What you will learn</h4><ul><li>Understand the architecture and components of the generative AI stack</li><li>Explore the role of vector databases in enhancing AI applications</li><li>Master Python frameworks for AI development</li><li>Implement Vector Search in AI applications</li><li>Find out how to effectively evaluate LLM output</li><li>Overcome common failures and challenges in AI development</li></ul><h4>Who this book is for</h4>This book is for software engineers and developers looking to build intelligent applications using generative AI. While the book is suitable for beginners, a basic understanding of Python programming is required to make the most of it. |
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System details note | Mode of access: Internet. |
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Personal name | Ben Perlmutter |
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Personal name | Thomas Rueckstiess |
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Personal name | Henry Weller |
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Personal name | Richmond Alake |
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Personal name | Shubham Ranjan |
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Corporate name or jurisdiction name as entry element | PACKT |
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Title | Building AI Intensive Python Applications |
Place, publisher, and date of publication | GB,Packt,2024-09-06 |
Physical description | 298 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://learning.packt.com/product/476805">https://learning.packt.com/product/476805</a> |
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