Synthetic

Building and testing machine learning models requires access to large and diverse data. But where can you find usable datasets without running into privacy issues? This practical book introduces techniques for generating synthetic data—fake data generated from real data—so you can perform secondary analysis to do research, understand customer behaviors, develop new products, or generate new revenue.

The first synthetic peptides were produced a century ago. In the ensuing period, they have developed as valuable research tools that are readily available to all researchers.