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SDK Notebooks
Jupyter notebook-based tutorials for popular use cases around synthetic data.

Docs

Examples

Notebook
Launch
Description
Open in Colab
Walk through the basics of using Gretel's Python SDK to create a synthetic dataset from a Pandas DataFrame or CSV.
Open in Colab
Train a synthetic model locally and generate data in your environment.
Open in Colab
Smart seeding is helpful when you want to preserve some of the original row data (primary keys, dates, important categorical data) in synthetic datasets.
Create synthetic time-series data from a Pandas DataFrame or CSV.
Use a synthetic model to boost the representation of an extreme minority class in a dataset by incorporating features from nearest neighbors.

Videos

Walk through creating synthetic data with Gretel.ai, Python, Pandas, and Jupyter.
Last modified 3mo ago
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