eabarnes1010/ml_tutorial_csu eabarnes1010/ml_tutorial_csu

  • Stars
    star
    2
  • Language
    Jupyter Notebook
  • License
    MIT License
  • Created over 2 years ago
  • Updated over 2 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
eabarnes1010/ml_tutorial_csu
github

eabarnes1010

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

material for the CSU-led machine learning tutorial for earth science research

More Repositories

1

controlled_abstention_networks

Neural network loss functions for regression and classification tasks that can say "I don't know".
Jupyter Notebook
12
star
2

course_ml_ats

machine learning for the atmospheric sciences - a CSU course
Jupyter Notebook
9
star
3

tlltt

This Looks Like That There: Interpretable neural networks for image tasks when location matters
Jupyter Notebook
7
star
4

course_objective_analysis

material for ATS 655 - Objective Analysis
Jupyter Notebook
6
star
5

actm-sai-csu

AI to detect, attribute, and quantify solar radiation management (SRM) effects and risks under a range of geopolitical scenarios. Project funded by DARPA‐PA‐21‐04‐02.
Python
6
star
6

hurricane_uqcomparisons

comparing different uncertainty quantification methods for neural network hurricane predictions
Jupyter Notebook
6
star
7

ml-hfi

A machine-learning based human footprint index, v1.0.
3
star
8

shash_tfp

SinhArcsinh in tensorflow-probability with additional custom functions
Jupyter Notebook
2
star
9

ai_weather_to_climate_ats780A8

materials for CSU ATS Weather-to-Climate Data Driven Forecasting
1
star
10

arise_perceived_failure

analysis code for paper on the potential for perceived failure under ARISE-SAI
Jupyter Notebook
1
star
11

tcane_fortran

Joint Hurricane Testbed (JHT) project using neural networks to predict a conditional distribution
Fortran
1
star