RMS 6110 — Introduction to Machine Learning for Image Data

3 semester hoursGraduateLecture

Explores a range of machine learning routines, including image classifications and clustering, PCAs, and data reduction. Students perform exercises corresponding to concepts introduced in weekly lessons. Focuses on computer thinking, algorithms involved in preprocessing, spectral and spatial enhancement, spatial analysis, and linear transformations. Utilizes a variety of data types and an opportunity to experience the journey of geospatial image data from its origin (raw data) to its end (transformation) in the context of the process, scope, and real-world scenarios. Examples provided with GBDX notebooks and customized work flows as entry to Python, cloud-based analytics, and web-based GUI software: ENVI, ArcGIS, and GBDX.

Prerequisites

Links

Official catalog (RMS course descriptions) · All RMS courses · Plan it at numap.app

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 "retiredSince": "2026-09-03"
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