Data Strategy for LLMs
Build reliable AI applications with RAG, fine-tuning, evaluation, and context engineering
$78.76
- Paperback
452 pages
- Release Date
30 October 2026
Summary
Learn the essential data techniques for building real-world LLM applications with this practical guide for technical professionals and advanced students, starting from data fundamentals to LLM-specific methods and advanced topics.
Key Features
- Learn state-of-the-art data strategies and techniques for LLM application development
- Understand the fundamentals of data collection, processing, and synthetic data generation
- Utilize LLM-specific…
Book Details
| ISBN-13: | 9781806116997 |
|---|---|
| ISBN-10: | 1806116995 |
| Author: | Eslam Kamal, Rany ElHousieny, Yash Sheth |
| Publisher: | Packt Publishing Limited |
| Imprint: | Packt Publishing Limited |
| Format: | Paperback |
| Number of Pages: | 452 |
| Release Date: | 30 October 2026 |
| Dimensions: | 191mm x 235mm |
Eslam Kamal
Eslam Kamal is an applied AI leader with 20 years of professional experience, including roles at Microsoft and Meta. His work spans natural language understanding, responsible AI, multimodal AI, and conversational AI systems. At Microsoft Research, he worked on language understanding. He later led applied science work across Microsoft Copilot, GitHub Copilot, and Azure Responsible AI. At Meta, he focused on conversational quality for Meta AI on Ray-Ban Meta glasses. He subsequently returned to Microsoft to lead applied AI for Dynamics 365 Contact Center. His experience has shaped a practical focus on how training and evaluation data influence model behavior and the reliability of deployed AI systems.
Rany ElHousieny is an AI solutions architect and senior AI engineering manager with over two decades of experience in AI, NLP, and ML. He spent 20 years at Microsoft, including time at Microsoft Research. Currently, he manages generative AI engineering teams at Clearwater Analytics, building retrieval, context engineering, and multi-agent systems for investment management. On Medium and LinkedIn, he writes regularly about AI systems architecture, RAG, multi-agent orchestration, context engines, and knowledge graphs. He also created the Agentic Repos framework that Chapter 11 builds on and was the technical reviewer of LLM Engineer’s Handbook (Packt).
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