Covers the basics of image processing for Earth observation, including course objectives, administration details, interdisciplinary aspects, and key image processing concepts.
Covers a review of machine learning concepts, including supervised learning, classification vs regression, linear models, kernel functions, support vector machines, dimensionality reduction, deep generative models, and cross-validation.
