Practical AI: Machine Learning, Data Science, LLM cover image

Practical AI: Machine Learning, Data Science, LLM

Cooking up synthetic data with Gretel

Feb 2, 2021
47:36

Podcast summary created with Snipd AI

Quick takeaways

  • Synthetic data aids in automated data labeling and differential privacy through closely resembling source data.
  • Complementary to anonymization, synthetic data is beneficial for imbalanced datasets like fraud detection.

Deep dives

Overview of Synthetic Data Generation

Synthetic data generation involves creating data that closely resembles source data, relying on machine learning and artificial intelligence to learn the semantics of the original dataset. By understanding these semantics, models can be built to generate records that convey the same overall story as the source data, allowing for running aggregate queries to extract similar insights. The process is essential for ensuring data privacy and balancing utility and privacy concerns.

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