Skip to content

Remove plaitpy, because not updated in 6 years #4

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
jackiekazil wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Remove plaitpy, because not updated in 6 years #4

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 0 additions & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,6 @@ Inspired by [Awesome Synthetic Data](https://github.com/gretelai/awesome-synthet
+ [Generative adversarial nets for synthetic time series data](https://github.com/stefan-jansen/synthetic-data-for-finance): a repository that shows how to create synthetic time-series data using generative adversarial networks (GANs).
+ [Gretel.ai](https://gretel.ai/): commercial synthetic data vendor that offers open source functionality.
+ [mirrorGen](https://github.com/DataResponsibly/MirrorDataGenerator): a python tool that generates synthetic data based on user-specified causal relations among features in the data.
+ [Plait.py](https://github.com/plaitpy/plaitpy): a program for generating fake data from composable yaml templates.
+ [Pydbgen](https://github.com/tirthajyoti/pydbgen): a Python package that generates a random database table based on the user's choice of data types.
+ [Smart noise synthesizer](https://smartnoise.org/): a differentially private open source synthesizer for tabular data.
+ [Synner](https://github.com/huda-lab/synner): an open source tool to generate real-looking synthetic data by visually specifying the properties of the dataset.
Expand Down