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#streamlit

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🌊 As I wanted to explore how combining multiple data sources can improve marine detection, I built a simple toy model using hydrophone data and marked individual tracking methods to estimate cetacean densities. I simulate the movement of individuals with a simple Individual-Based Model (IBM), and for the density estimation, I’ve used Kernel Density Estimation (KDE), though other techniques like Kriging could also be applied.

You can explore the model through this Streamlit web app:
antoinebrias-ocean-detection-s

For more details on the project, check out my full article here:
briaslab.fr/blog/?action=view&

Hails #metalheads!
Check out my new site to research and discover #metal 🤘
randommetaltools.streamlit.app
Five tools at the moment:
- Random Metal Record with its link to Spotify
- Random Metal Record from Bandcamp with embedded player
- Random New Release with links to Spotify and/or Bandcamp.
- Random by Genres: Pick a genre and search a random record with links to Spotify and/or Bandcamp.
-Lastfm manual scrobbler
#heavymetal #deathmetal #blackmetal #doommetal #grindcore #powermetal #python #streamlit #coding

Excited to announce a little tool I developer call auto-dashboards to my Mastodon friends!

This is a JupyterLab extension that lets you convert your notebooks into interactive dashboards — or run your existing ones — all in one click. Streamlit and Solara are supported at the moment. And yes, it uses AI to run the translation :AngeryCat:

📦 Available on PyPI: pip install auto-dashboards
ℹ️ Source code: github.com/orbrx/auto-dashboar