5. 1.5 Lecture Hour. Machine learning methods for data science in energy systems, with focus on predictive models and evaluation techniques for understanding performance models; topics include supervised learning, classification, predictive models, performance evaluation, neural networks, and deep learning with different data types. Prerequisites: Graduate classification; ENGY majors; ENGY 640 or approval of instructor Credit 1.
5. 1.5 Lecture Hour. Machine learning methods for data science in energy systems, with focus on predictive models and evaluation techniques for understanding performance models; topics include supervised learning, classification, predictive models, performance evaluation, neural networks, and deep learning with different data types. Prerequisites: Graduate classification; ENGY majors; ENGY 640 or approval of instructor Credit 1.
