University of Houston 3 credits MECE
Prerequisite: Engr 1331; Math 3321; MECE 3338; Fluency in Matlab; Extensive knowledge of Linear Algebra. This course introduces the-state-of-the-art in the field and covers topics, such as, engineering data pre-processing methods, K-nearest neighbor (KNN), decision tree, linear regression. Logistic regression, support vector machine (SVM), conditional probability & Naïve Bayes Classifier, Hidden Markov Model (HMM), back propagation (BP) neural network, recurrent neural network (RNN), convolutional neural network (CNN), Clustering, and their applications. Most machine learning methods will be accompanied by mechanical engineering application examples.
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