Name: David John Gagne
Type: User
Company: NSF National Center for Atmospheric Research
Bio: Machine Learning Scientist II and head of the Machine Integration and Learning for Earth Systems group at the NSF National Center for Atmospheric Research.
Location: Boulder, CO
Blog: https://staff.ucar.edu/users/dgagne
David John Gagne's Projects
American Meteorological Society LaTeX Stuff
Machine Learning in Python for Environmental Science Problems AMS Short Course Material
Data from the 2008 AMS AI Competition on predicting storm mode
Weather forecasting display and analysis package developed by NWS/Raytheon, released as open source software by Unidata.
California Rainfall Prediction Hackathon for Climate Informatics 2017
Processing code for Climate Informatics Hackathon 2017.
Streaming and approximate algorithms. WIP, use at own risk.
Data and code behind the stories and interactives at FiveThirtyEight
Interpretable Deep Learning for Spatial Analysis of Severe Hailstorms
Dissertation hail verification notebooks
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Deep Learning Demo for the ASP Summer Colloquium 2019
Ready-to-run Docker images containing Jupyter applications
Testbed for autoencoding different kinds of fields.
End-to-end machine-learning library for predicting thunderstorm hazards.
GOES-16 Convective Initiation Benchmark
HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.
Hagelslag supports segmentation and tracking of weather fields and scalable verification, including performance diagrams and reliability diagrams.
Object-based severe weather forecasting system.
Shared code for the evaluation of hail forecast models.
A series of Jupyter notebooks that walk you through the fundamentals of Python, Scientific Computing and Visualization, Machine Learning in Python, etc.