1. FAQs
  2. Gretel-synthetics

Gretel-synthetics FAQs

What is synthetic data?

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How does Gretel synthetics create artificial data?

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Is there an architecture diagram?

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What kinds of data can I send to Gretel-synthetics?

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What are the outputs from Gretel-synthetics?

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Can I run gretel-synthetics on premises?

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What are gretel-synthetics premium features?

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Do I still need to de-identify sensitive data when using gretel-synthetics?

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What kinds of privacy protections can Gretel Synthetics help with?

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How is Gretel-synthetics differential privacy different from traditional implementations?

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How is synthetic data different from the original source data it was trained on?

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How many lines of input data do I need to train a synthetic model?

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How many columns of training data can I have?

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How many epochs should I train my model with?

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Does training a synthetic model require a GPU?

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What is differential privacy?

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How does Gretel-synthetics leverage differential privacy?

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How does Gretel-synthetics implement differential privacy?

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If my model trained in batches using differential privacy, what is my final epsilon (privacy guarantee)?

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What are good epsilon (ε) and delta (δ) values in differential privacy?

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How is Stochastic Gradient Descent (SGD) modified to be differentially private?

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What does RDP order mean?

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