Double Descent Curves: Overparametrization

This lecture by the instructor covers the mathematics of data, focusing on the transition from theory to computation. Topics include the trade-off between model complexity and risk, the dangers of complex function classes leading to overfitting, the benefits of overparametrization, and the generalization mystery in deep learning. The lecture delves into the concept of double descent curves, exploring the implications of overparametrization in machine learning models.