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Generative Neural Architectures-Design Patterns, Model Adaptation, and Production Operations (Tech Trends) - Softcover

Mahir, Atheer

 
9798237266665: Generative Neural Architectures-Design Patterns, Model Adaptation, and Production Operations (Tech Trends)

Synopsis

Large language models are easy to call and hard to run well. Generative Neural Architectures walks through the whole path in plain language: how the transformer predicts text, how to choose a model, how to build applications around it, when to adapt it, and how to keep it reliable and affordable once real users depend on it.

Every chapter explains an idea, turns it into working code and traces it back to the research it came from.

Inside you will learn:
- Foundations: tokens, embeddings, attention and how to read benchmarks with care
- Building: message roles, streaming, prompt design and retrieval-augmented generation
- Adapting: when to fine-tune, LoRA and QLoRA, and how to evaluate the result, with a real fine-tuning run reported step by step
- Operating: deployment choices, quantization, pruning, distillation, monitoring and guardrails

Written for software engineers entering the field and for practitioners who design, adapt and run these systems in production.

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About the Author

Atheer Mahir, a leading AI engineer and researcher with over three decades of experience across varied sectors, is also an accomplished author with several published books. Holding advanced degrees in Science, Computer Science, Mathematics, and Physics, he exhibits a profound command of diverse programming languages. His expertise in AI is further distinguished by a creative approach, particularly visible in his specialization in photography. Committed to lifelong learning, Mahir enhances his knowledge through many platforms like LinkedIn Learning and Coursera. As a recognized authority on AI detection tools, he counsels against their use in academic settings due to their potential inaccuracies. Mahir's innovative work, coupled with his advisory insights, plays a crucial role in the advancement of AI applications in education and research.

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