The University of Texas at Austin 3 credits Petroleum and Geosystems Engineering
Explore fundamental probability and statistics; inference and prediction; and model training, testing, tuning, and validation. Examine workflows for integrating many features; workflows for anomaly detection, spatiotemporal prediction, and uncertainty integration. Communicate results within a project team to impact subsurface decision making. Petroleum and Geosystems Engineering 379 (Topic: Subsurface Machine Learning) and 379 (Topic 9) may not both be counted. Three lecture hours a week for one semester. Pre/Corequisites: Mathematics 408D or 408M with a grade of at least C-.
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