Radiant MLHub is an open library for geospatial training data to advance machine learning applications on Earth Observations. It serves as a resource for a community of practice, giving data scientists benchmarks they can use to train and validate their models and improve its performance. Datasets include pairs of imagery and labels for different ML problem types including image classification, object detection, and segmentation. Radiant MLHub catalogs datasets using a SpatioTemporal Asset Catalog (STAC) spec and exposes them through a common API

This workshop will be a hands-on tutorial in using the Radiant MLHub Python client to download datasets and train a basic machine learning model. A working knowledge of Python programming is required and some familiarity with training machine learning models in Python is recommended.