Synthetic Data Tutorials¶
Explore synthetic data tutorials with the option to run them either in Google Colab or open them in VS Code.
| Description | Colab Link | Notebook Link |
|---|---|---|
| Getting Started with the SDK | View Notebook | |
| Validate synthetic data via Train-Synthetic-Test-Real | View Notebook | |
| Explore the size vs. accuracy trade-off for synthetic data | View Notebook | |
| Differentially Private Synthetic Data | View Notebook | |
| Rebalance synthetic datasets for data augmentation | View Notebook | |
| Conditionally simulate synthetic (geo) data | View Notebook | |
| Explain AI with synthetic data | View Notebook | |
| Generate fair synthetic data | View Notebook | |
| Generate synthetic text via a fast LSTM model trained from scratch | View Notebook | |
| Generate synthetic text via a pre-trained Large Language Model | View Notebook | |
| Perform multi-table synthesis | View Notebook | |
| Analyse star-schema correlations | View Notebook | |
| Develop a fake or real discriminator with Synthetic Data | View Notebook | |
| Close gaps in your data with Smart Imputation | View Notebook | |
| Calculate accuracy and privacy metrics for Quality Assurance | View Notebook | |
| Enrich Sensitive Data with LLMs using Synthetic Replicas | View Notebook | |
| MOSTLY AI vs. SDV comparison: single-table scenario | View Notebook | |
| MOSTLY AI vs. SDV comparison: sequential scenario | View Notebook |