Machine Learning Fundamentals

CST

4702

Machine Learning Fundamentals

Introduces fundamental machine learning algorithms and techniques, and their applications to solving realworld problems. Topics include supervised learning (parametric/non-parametric algorithms, support vectormachines, kernels, neural networks), unsupervised learning (clustering, dimensionality reduction,recommender systems, deep learning) and best practices in machine learning (bias/variance theory;innovation process in machine learning). The theory of machine learning and practical know-how lead tonumerous case studies with applications in text understanding (web search, anti-spam), medicalinformatics, audio, database mining and other areas.

033680

No

WRIC - WRIC (Writing Intensive)