BLG 527E - Machine Learning
Course Objectives
This course will provide students an overview of issues, algorithms and techniques in machine learning. Students will also gain theoretical and practical experience through programming exercises and projects.
Course Description
Introduction, Cross Validation; Supervised, Unsupervised and Semi-Supervised Learning; Feature and Sample Selection; Dimensionality Reduction; Clustering; Classifiers; Regressors; Ensemble Methods (Combining Multiple Learners); Decision Trees; Linear Dicrimination; Support Vector Machines; Multilayer Perceptrons; Parametric Methods; Multivariate Methods; Evaluation and Assessment Metrics/Criteria
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Course Coordinator
Yusuf Yaslan
Course Language
English
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