Covers the binary choice model, error term assumptions, specific constants, invariances, and distribution properties.
Explores the regulation of therapeutic products, covering legal requirements, product classification, market access, and advertising rules.
Explores generalization error in machine learning, focusing on data distribution and hypothesis impact.
Explores the benefits of deeper networks in deep learning and the importance of over-parameterization and generalization.
Introduces linear programming basics, including optimization problems, cost functions, simplex algorithm, geometry of linear programs, extreme points, and degeneracy.
