FUNDAMENTALS OF MACHINE LEARNING FOR EARTH OBSERVATION NASA ARSET
- Assesement/Assignment Upon course completion and certificate request!
Trainers: Jordan A. Caraballo-Vega, Caleb Spradlin, Jian Li, Jules Kouatchou
- Overview of Machine Learning
- Importance of Machine Learning targeted towards Earth Science
- Usability of Machine Learning
- Software to Support Machine Learning
- Machine Learning Applications
- Hands on Jupyter Notebook Exercise: Load and Visualize Data
- Post-session assignment
- Q&A Session
Trainers: Jordan A. Caraballo-Vega, Caleb Spradlin, Jian Li, Jules Kouatchou
- Download the training data
- Exploratory data analysis
- Extracting training data from tabular dataset
- Extracting training data from raster dataset
- Training and inference of tabular and raster dataset
- Metrics and model evaluation
- Hands on Jupyter Notebook Exercise: MODIS Water Classification Case Study
- Post-session assignment
- Q&A Session
Trainers: Jordan A. Caraballo-Vega, Caleb Spradlin, Jian Li, Jules Kouatchou
- Overview of model tuning
- Overview of parameter optimization
- Exercise to optimize existing model
- Overview of model explainability and interpretability
- Overview of additional machine learning algorithms
- Hands on Jupyter Notebook Exercise: Improvements to MODIS Water Classification Model
- Post-session assignment
- Q&A Session
- Assesement/Assignment Upon course completion and certificate request
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