Synthetic Data Generation with AI: A Practical Guide to Creating, Evaluating, and Governing Artificial Data

Every machine learning project depends on data, and real data is often the hardest part. It may be locked behind privacy rules, too rare to learn from, too costly to label, or missing entirely. This book shows you how to solve that problem with synthetic data: artificial records that behave like the real thing, without the barriers.

Written in clear, plain language, Synthetic Data Generation with AI walks you from first principles to working practice. You’ll learn the full range of methods, from simple rules and statistical sampling to GANs, VAEs, diffusion models, and large language models. You’ll see how to generate tabular, time-series, text, image, and code data, and how to write prompts that produce varied, realistic results instead of repetitive output.