Idézet:Data Management for AI and Agentic Systems offers a foundational guide to designing robust data pipelines for AI models and agents. As demand for AI-driven decision-making grows, many systems fail because of poor or unreliable data. This book focuses on a critical-but often overlooked-component of success: structured, trustworthy, and context-rich data.

Author Michael Bachman draws on decades of experience to bridge the gap between data engineering and AI development. With practical strategies, case studies, and real-world code examples, readers will learn to align AI and data systems for greater accuracy, scalability, and performance in production environments.

Solve challenges in data quality, governance, and ingestion
Prevent failures like hallucinations and model drift with better data
Design agent-ready datasets rooted in domain-specific structure
Automate data validation and monitoring to maintain trust
Align data workflows with modern AI and agentic architectures

Idézet:? Data Management For AI & Agentic Systems 9798341649545.epub (Michael Bachman) (2025) (2.53 MB)

Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.

Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.