Synthetic Data and Generative AI 1st Edition

Grab attention with cutting-edge insight into one of AI’s most transformative tools: Synthetic Data and Generative AI, 1st Edition by Vincent Granville. This compact, authoritative guide makes complex concepts accessible for practitioners and decision-makers alike.

Explore clear, practical explanations of how synthetic data is created and applied across industries—finance, healthcare, retail, and government—along with real-world examples of generative models, privacy-preserving techniques, and data augmentation strategies. Granville balances theory with actionable guidance so readers can assess risks, improve model robustness, and comply with evolving data regulations.

Perfect for data scientists, machine learning engineers, product managers, and policy professionals, the book covers model selection, quality metrics for synthetic datasets, bias mitigation, and deployment best practices. Emphasis on ethical design and privacy ensures the content is relevant for teams operating in North America, Europe, Asia, and global markets seeking GDPR- and CCPA-aware approaches.

Why this edition matters: it equips you to reduce dependency on sensitive production data, accelerate experimentation, and scale AI initiatives while maintaining compliance and trust. Packed with practical tips, decision checklists, and illustrative case studies, the text helps translate generative AI concepts into measurable business value.

Ready to modernize your data strategy? Add Synthetic Data and Generative AI, 1st Edition to your professional library today and gain a competitive edge in building responsible, high-performance AI systems worldwide.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.