## Associated Tutorial This workflows is part of the tutorial [A Docker-based interactive Jupyterlab powered by GPU for artificial intelligence in Galaxy](https://training.galaxyproject.org/training-material/topics/statistics/tutorials/gpu_jupyter_lab/tutorial.html), available in the [GTN](https://training.galaxyproject.org) ## Thanks to... **Tutorial Author(s)**: [Anup Kumar](https://training.galaxyproject.org/training-material/hall-of-fame/anuprulez/) **Tutorial Contributor(s)**: [Saskia Hiltemann](https://training.galaxyproject.org/training-material/hall-of-fame/shiltemann/), [Helena Rasche](https://training.galaxyproject.org/training-material/hall-of-fame/hexylena/), [Kaivan Kamali](https://training.galaxyproject.org/training-material/hall-of-fame/kxk302/), [Anup Kumar](https://training.galaxyproject.org/training-material/hall-of-fame/anuprulez/), [Björn Grüning](https://training.galaxyproject.org/training-material/hall-of-fame/bgruening/), [Martin Čech](https://training.galaxyproject.org/training-material/hall-of-fame/martenson/), [Armin Dadras](https://training.galaxyproject.org/training-material/hall-of-fame/dadrasarmin/) **Funder(s)**: [ELIXIR Europe](https://training.galaxyproject.org/training-material/hall-of-fame/elixir-europe/), [de.NBI](https://training.galaxyproject.org/training-material/hall-of-fame/deNBI/), [University of Freiburg](https://training.galaxyproject.org/training-material/hall-of-fame/uni-freiburg/) **Grants(s)**: [EuroScienceGateway](https://training.galaxyproject.org/training-material/hall-of-fame/eurosciencegateway/) [](https://training.galaxyproject.org/training-material/)