DATA 471 - 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: CSCI 241; MATH 204; MATH 224; and MATH 341.
Credits: 4
Grade Mode: Letter