Machine Learning in Geosciences

4 credits

Provides introduction to machine learning in geosciences, basics of computing, and methodologies in applied machine learning. Focuses on canonical and topical data sets in seismology, oceanography, cryosphere, planetary sciences, geology, and geodesy. Topics include unsupervised clustering, logistic regression, random forest, support vector machine, and deep learning. Recommended: either knowledge in Matlab or Python, AMATH 301, or 100- or 200-level ESS, ATM S, or OCEAN courses in earth sciences. Offered: A.