This site is ARCHIVED and will NO LONGER BE UPDATED.
For updated Tutorial material, please visit the Pythia landsat-ml cookbook.
For Topic Examples, head over to the HoloViz Examples website.


Right click to download this notebook from GitHub.

The EarthML tutorial takes you through the various stages involved in using Python open-source tools to work with machine-learning and related data analysis tools for climate and other Earth science topics:

  1. Data Ingestion: Loading large data sets efficiently with intake.
  2. Introduction to Visualization: How to visualize data loaded into memory.
  3. Alignment and Preprocessing: How to prepare your data for the machine learning pipeline.
  4. Machine Learning: Specifying a scikit-learn pipeline to ingest the prepared training data.
  5. Data Visualization: How to visualize your data throughout the workflow, starting from data ingestion to the final machine learning product.