ECE-5464: Applications of Machine Learning

Description: Applications of Machine Learning (ML) for predictive data analytics. Probability for ML including conditional probability, the product and chain rule, and the Theorem of Total Probability. Data preparation for ML algorithms, normalization, cleaning, and imputation of missing values. Information-based learning using decision trees. Similarity-based methods, data classification and clustering. Probability-based learning, conditional probability and Bayes’ theorem, and applications. Linear and logistic regression and optimization-based learning. Performance evaluation of ML systems. Artificial Neural Networks. Real-world applications of ML and case studies. Not for CPE-MS, EE-MS, CPE-PhD, or EE-PhD credit. May be taken for CPE-MEng or EE-MEng credit. Pre: Graduate Standing.

Pathways: N/A

Course Hours: 3 credits

Corequisites: N/A

Crosslist: N/A

Repeatability: N/A