SDV

I'm working on the Synthetic Data Vault, a set of libraries to generate realistic synthetic data. We have an option to use GAN models but we've found that Gaussian & other copula models work great because they're faster and more user configurable. https://github.com/sdv-dev/SDV

Can someone help me understand the licensing of this? https://github.com/sdv-dev/SDV/blob/main/LICENSE It was MIT licensed up until 2022 where it was changed to what it is now, where they say that it will become MIT again 4 years after release... but is that from when the license was changed or the first release of the software in GitHub?

For those wanting to learn more about it, SDV can be found here: https://github.com/sdv-dev/SDV SDV (The Synthetic Data Vault) is an ecosystem of Open Source Python libraries and tools for Synthetic Data Generation that works with single-table, multi-table and time-series data. One of the use cases of Synthetic Data is data augmentation for machine learning models, as shown in the example posted, but it also enables a multitude of other use cases such as privacy preserving methods for sharing data or the generation of data for software testing. More resources, tutorials and documentation can be also found here: https://sdv.dev

Yes, I think it's more about Synthetic Data Generation than versioning. Much closer to what SDV [0] does. [0] https://github.com/sdv-dev/SDV

It is becoming clearer every day how Synthetic Data Generation will be a must-have skill and technology in the upcoming years! I'm the lead developer of an Open Source project called SDV (The Synthetic Data Vault)[0] which offers an ecosystem of Python libraries and resources for Synthetic Data Generation of different data modalities. It allows learning and sampling synthetic clones of Single Table, Relational and Time Series datasets, and offers tools to evaluate the quality of the generated data and benchmark different models. [0] https://github.com/sdv-dev/SDV