Practical Synthetic Data Generation: Balancing Privacy and the Broad Availability of Data by Khaled El Emam, Lucy Mosquera, Richard Hoptroff
English | May 19th, 2020 | ISBN: 1492072745 | 166 pages | EPUB | 8.27 MB
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.