MACHINE LEARNING CHALLENGES IN THE REAL WORLD

Catalog description

Explores the challenges that machine learning systems face when they move from the laboratory into the real world. Topics include thorny (but common) obstacles such as missing values, correlated data, concept/domain shift, evaluation, explainability, and more. Provides the opportunity for students to apply these concepts and strategies on a data set of their choice.