Explore projects

Short tutorial about plotting with Pandas in Python

Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. Based on the open source software JupyterLab, a way has been a

http://slms.pages.jsc.fz-juelich.de/websites/all-website/

A library of Python utilities developed at the Simulation and Data Laboratory Neuroscience, and the High Performance Computing in Neuroscience (HPCNS) division of the Jülich Supercomputing Center.

Here is the repository of the on-going project to develop a stand-alone sager with Python to using for I/O, Pre/Post-Processing

Accelerating hyperparameter tuning for Remote Sensing by switching the batch size during training

Mapping of ozone data with machine learning methods.

Houses the code base for OpenGPT-X, based on BigScience.

Team1 Counting Leaf!