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pip_desc.md

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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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# GANs for tabular data
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<img src="https://raw.githubusercontent.com/Diyago/GAN-for-tabular-data/e5a4d437655261755de962b9779c73203611d921/images/logo%20tabular%20gan.svg" height="15%" width="15%">
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We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.
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* Github project: ["GAN-for-tabular-data"](https://github.com/Diyago/GAN-for-tabular-data)

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