/AIML_Class

Training materials on AI/ML in Heliophysics

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Center for HelioAnalytics

Machine Learning Tutorial

Brought to you by:

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This series of tutorials was developed for the 2024 Python in Heliophysics Summer School held May 20-24, 2024. They have been adapted for use as a self-guided learning course.

Machine Learning Tutorial Course Materials

Session Lecture Topic Link Timing
Session 1 Introduction
Session 1A What is Machine Learning? Link
Session 1B How does Machine Learning work? Link
Session 2 Examples: ML Models
Session 2A Clustering Link
Session 2B Decision Boundary Link
Session 2C Decision Boundary using TensorFlow Link
Session 2D Classifier Link
Session 3 Data Science Workflow Link

Use and Dependencies

These materials were developed for the summer school students, but are intended to function as stand-alone lessons freely to be used by anyone.

The lessons use the following packages: numpy, pandas, matplotlib, and tensorflow (keras).

Acknowledgments

These course materials were developed by the Center for HelioAnalytics (CfHA) with the support of funding from NASA. We request that any subsequent use acknowledge CfHA.

The course materials were derived in part from the 2022 NASA EPSCOR Hack Week hosted by West Virginia University.

In adddition to the Center for HelioAnalytics team members, we want to acknowledge the following authors for their major contributions to these course materials:
Evana Gizzi, Ph.D., AI Researcher NASA GSFC
Richard Licata, Ph.D., Data Scientist, CACI International

Additional Resources

Books and texts

Online articles