Mapping from Training Data to Predictions with Datamodels - Differential Privacy in Machine Learning
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the intricacies of machine learning predictions and data models in this Google TechTalk presented by Andrew Ilyas. Delve into the anatomy of machine learning predictions, understanding datamodels and their role in the ML pipeline. Learn about model output functions, data generation techniques, and the construction of linear models and training sets. Discover how to construct and evaluate data models, and explore their applications in addressing model brittleness and data counterfactuals. Examine example embedding, natural similarity metrics, and spectral clustering. Gain valuable insights and takeaways from this comprehensive exploration of mapping training data to predictions using datamodels.