ZetaGAN

A Data Augmentation Platform.

專案需求
Web front-end.
AI or Data Scientist.
專案內容

 

Inspiration

  • Collecting data takes time: AI is powerful when there are numerous labelled data to train the model; however, data collection is time-consuming.
  • Imbalanced data: Imbalance is common and expected in real world, e.g. Medical diagnosis, Spam filtering, and Fraud detection.
  • Concern of data privacy: The concerns of data leak and privacy are increasing. It’s getting harder and harder to collect data due to new regulations and guidelines, e.g. GDPR.

What it does

  • Generate Synthetic Samples, i.e. pseudo data, for structured/tabular data.The data’s schema, data distribution, and relationship between columns of the generated data are as close to real data as possible.The difference of statistical properties between synthetic and real data is slight.
  • A Data Augmentation Platform to provide the data augmentation service with only small amount of data.
目前進度
40%
We have trained the augmentation model using AI techniques, and developed the Web UI for our platform.
​加入本專案的成員們:

Mei-Chen Chu

發起者

Albert Chen

I am an Al engineer / Data scientist.

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