• UNM

Introduction to Machine Learning

CS 529 / 429 (3)

Introduction to principles and practice of systems that improve performance through experience. Topics include statistical learning framework, supervised and unsupervised learning, Bayesian analysis, time series analysis, reinforcement learning, performance evaluation and empirical methodology; design tradeoffs.

Prerequisite: 362 or 530 or 561.

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Prerequisites / Corequisites

Data Structures and Algorithms II - CS 362

Geometric and Probabilistic Methods in Computer Science - CS 530

Algorithms/Data Structure - CS 561

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