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Using Synthetic Data for Machine Learning & AI in Python

Wednesday July 5, 11 AM ET

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.

Your Presenter(s)

Alexandra Ebert headshot

Alexandra Ebert

Chief Trust Officer at MOSTLY AI

Alexandra is an expert in data privacy and responsible AI. She works on public policy issues in the emerging field of synthetic data and ethical AI. In addition to her role as Chief Trust Officer at MOSTLY AI, Alexandra is the chair of the IEEE Synthetic Data IC expert group and the host of the Data Democratization podcast.

Why this matters

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.

Join 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!

Register for the webinar

Al continuar, aceptas nuestros Términos de uso, nuestra Política de privacidad y que tus datos se almacenen en los EE. UU.

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