DATA 571 - Machine Learning

Key machine learning theory, algorithms and experimentation techniques. Generalization, bias and variance. Classification, regression, clustering and probabilistic modeling. Linear models and neural networks. Discrete and continuous optimization algorithms. Ethical issues in machine learning.

Prerequisites & Notes: Graduate status; MATH 204; MATH 224; and MATH 341; or instructor permission.
Credits: 4
Grade Mode: Letter