Drexel University 3 credits ECE
This course introduces students to topics in modern machine learning, along with applications of machine learning to problems in engineering. Introductory topics will include an overview of classification, overfitting, cross-validation, and dimensionality reduction. Supervised classification approaches will be covered including linear classifiers, generative and discriminative models, non-probabilistic classification approaches, kernel methods, and neural networks. Topics in unsupervised learning will also be covered if time permits.
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