Decision-Tree Methods in Hydrological Modeling Workshop

Machine Learning: Decision Tree Models for Post-Processing National Water Model Streamflow Outputs

Day 4 Session 2 (11:00 AM MDT)

The Decision-Tree workshop will explore simple Decision Trees, Random Forest, and XGBoost in streamflow modeling. The workshop will include a brief introduction to decision tree algorithms and transition to hands-on activities in which participants will engage in the ML development pipeline, including data processing, algorithm training, and model evaluation. The workshop will use the CIROH cloud and all of the Python code and data will be available through GitHub and public Amazon S3 buckets. Participants can expect an improved understanding of different decision tree algorithms and their applications within hydrological modeling, knowledge of data preprocessing, data visualization, and general skills in using Git and cloud computing workspace