# Hyperparameter optimization studies of an environmental use-case with InterTwin.

- Institution: CERN
- Department: CERN openlab Summer Student Programme 2024
- Speaker: Dorcas Mulaye
- Year: 2024
- Language: English
- Subjects: Earth and environment
- Source: [CERN](https://videos.cern.ch/record/3013909)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

In this study, we explore the effect of tuning hyperparameters in order to achieve the best model performance on an environmental AI-based model for drought predictions in the Alps developed by EURAC Trento in the context of InterTwin under the InterTwin Project. We begin with a brief introduction of both interTwin and the environmental use case, followed by a comparative analysis of different hyperparameter combinations, showcasing their impact on model accuracy, computational efficiency and overall predictive capability..

0:00:00 Slide 1

0:05:42 Slide 2

0:07:05 Slide 3

## Lectures

1. [Hyperparameter optimization studies of an environmental use-case with InterTwin.](https://invisiblenetwork.ai/learn/cern/3013909/55f3b2157910), 9 min (CERN's player)