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USDA-ARS/University of Florida Machine Learning Training

introduction to machine learning methods using Jupyter notebooks and coding excercises

SCINet Onboarding (Intro to SCINet)

SCINet and Ceres basics for new SCINet users, including HPC beginners

NEON High Resolution Hyperspectral Data Exercise

explore NEON AOP hyperspectral data, calculate/visualize spectral indices, unsupervised ML (clustering)

Geospatial Analysis with Python on Ceres

efficient data practices, using JupyterHub and Lab on Ceres, using Dask for parallel computing

Quantitative Trait Locus (QTL) Analysis for Breeding

use QTL-surge and RStudio on Ceres

Introduction to Unix (from the Bioinformatics Workbook)

a video and written tutorial on basic unix commands