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Introduction to Machine Learning for Climate Scientists

29–30 Mar 2023
DKRZ Main Building
Europe/Berlin timezone
  • Overview
  • Timetable
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Contact

  • arnold@dkrz.de

Contribution List

5 / 5
1. Introduction to Machine Learning
Caroline Arnold (Hereon, DKRZ)
29/03/2023, 13:00
Day 1
  • Get to know the typical workflow of a Machine Learning project
  • Recap the necessary Python concepts to write Machine Learning code
8. Examples for ML in Climate Science
Christopher Kadow
29/03/2023, 14:25
Day 1
3. Introduction to Pytorch
Etienne Plésiat
29/03/2023, 15:15
Day 1
  • Recap on Neural Networks and Convolutional Neural Networks (CNNs)
  • Setup the tutorials on the JupyterHub
  • Introduction to PyTorch with examples
6. PyTorch applied to Climate Science
Etienne Plésiat
30/03/2023, 09:00
Day 2

Using a simple example, we will see how to:
- Load/split a climate dataset
- Build a CNN
- Train the model
- Test the model

7. Introduction to using Pytorch on Levante
Johannes Meuer (DKRZ)
30/03/2023, 11:15
Day 2
  • Introduction to SLURM for job scheduling on Levante
  • Description of Advanced Use-Case
  • Training a computational expensive model on Levante

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