name: machine-learning-and-ai
description: "Use geemap machine learning conversion helpers and optional AI
dataset discovery interfaces."
disable-model-invocation: true
metadata:
disco-role: operating
license: MIT
geemap Machine Learning and AI
Use this sub-skill when a task involves geemap's Earth Engine classification workflows, local scikit-learn decision-tree/random-forest conversion into Earth Engine classifier strings, classifier CSV or FeatureCollection persistence, or optional AI-assisted Earth Engine dataset discovery.
Start here
- Confirm basic geemap, Earth Engine, and optional dependency setup with ../../references/installation-and-auth.md.
- For local model conversion, use references/workflows.md and the bundled scripts/rf_tree_smoke.py.
- For exact function signatures, inputs, outputs, and gotchas, use references/api-reference.md.
- For error handling, use references/troubleshooting.md.
What this sub-skill owns
geemap.ml.tree_to_string for one fitted scikit-learn decision tree.geemap.ml.rf_to_strings for fitted scikit-learn random-forest or ExtraTrees-style ensembles.geemap.ml.strings_to_classifier for in-memory Earth Engine classifier construction from tree strings.geemap.ml.trees_to_csv and geemap.ml.csv_to_classifier for local CSV persistence and reload.geemap.ml.export_trees_to_fc and geemap.ml.fc_to_classifier for Earth Engine asset FeatureCollection persistence and reload.- Earth Engine supervised/unsupervised classification workflow structure: sample training data, train or import a classifier/clusterer, classify an image, then route display or accuracy work to the sibling sub-skills.
- Optional
geemap.ai dataset catalog, Gemini/Genie, embedding, and dataset explorer surfaces when the ai extra, Google credentials, network access, and notebook UI are available.
Route elsewhere
- Generic file conversion, Earth Engine export tasks, shapefile/GeoJSON/CSV data movement, or non-classifier table export: ../conversion-and-io/SKILL.md.
- Adding classified images or vector layers to an interactive map: ../interactive-earth-engine-maps/SKILL.md.
- Accuracy matrices, charts, legends, palettes, static cartography, or chart rendering: ../visualization-and-charts/SKILL.md.
- Timelapse, GIF, app, or publication workflows: ../timelapse-and-apps/SKILL.md.
Operating constraints
- Local tree conversion is concrete and deterministic, but it requires scikit-learn, numpy, pandas, and a fitted compatible estimator.
- Earth Engine classifier objects can be constructed locally from strings, CSV, or FeatureCollections, but using them to classify images or export assets requires Earth Engine initialization, credentials, a project when required by the Earth Engine client, and network access.
- AI helpers are optional, credentialed, and networked. Treat them as convenience interfaces, not required geemap ML functionality.
- Do not rely on source notebooks or repository checkout files at runtime; the self-contained recipes and script in this sub-skill are the supported reference.