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Using Synthetic Data for Machine Learning & AI in Python

Rewatch this training to discover what synthetic data is, how it protects privacy, and how it's being used to accelerate AI adoption in banking, healthcare, and many other industries.
Alexandra Ebert
Alexandra Ebert

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80% of AI projects fail, and more don't even start due to privacy constraints. This is where AI-generated synthetic data comes in. It's an anonymization technology seen as the key enabler for artificial intelligence.

Rewatch this training to discover what synthetic data is, how it protects privacy, and how it's being used to accelerate AI adoption in banking, healthcare, and many other industries. You will create a highly representative synthetic dataset yourself, learn how to assess its quality and use it for privacy-preserving machine learning. And as a bonus exercise, we'll look into smart imputation with synthetic data to save you time on data pre-processing!

Key Takeaways:

  • Learn when synthetic data can be helpful for protecting privacy.
  • Learn how to create synthetic datasets.
  • Learn how to assess the quality of synthetic datasets.

Additional Resources

Code along with Alexandra on DataLab

Generate synthetic data using MOSTLY AI - Use the ‘AI/ML training’ set

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Machine LearningArtificial IntelligencePythonData Scientist

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