Winter 2023: Machine Learning Theory

Winter 2023: Machine Learning Theory

Course No:
EECS 598-014
Credit Hours:
3
Instructor:
Wei Hu
Prerequisites:
Mathematical maturity. Familiarity with probability, multivariate calculus, and linear algebra is required. Knowledge of machine learning is recommended but not required.

When do machine learning algorithms work and why? How do we formally characterize what it means to learn from data? This course will study the theoretical foundations of machine learning. Tentative topics include generalization, optimization, deep learning, online learning and bandits, and unsupervised learning.

 

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