Tabular synthetic data generation
Tabular synthetic data generation is a powerful method to create high-quality artificial datasets that mirror the statistical properties of original tabular data. A tabular dataset is usually composed by several columns with structured data and mixed data types (dates, categorical, numerical, etc) with not time dependence between records. This ability of generating synthetic data from this type of datasets is essential for a wide range of applications, from data augmentation to privacy preservation, and is particularly useful in scenarios where obtaining or using real data is challenging.
Tutorials & Recipes
To get-started with Synthetic Data Generation you can follow out quickstart guide.
For more tutorial and recipes, follow the link to YData's Academy.