Visualizing continental US and Alaskan earthquakes using GeoPandas. Geospatial data augmentation and machine learning to classify globally whether or not an earthquake triggers a tsunami risk. Analyzed results based on recall, ROC-AUC, precision, and F1 score.

Web based data visualisation project about natural disasters using d3.js

Machine learning algorithm to predict whether a tweet is about a real disaster or not

PyGMTSAR (Python InSAR): Powerful and Accessible Satellite Interferometry

Rescuer-seeker it's an application to detect live people, houses and vehicles with an aerial drone view for rescue operations after natural disasters.

Analyse des données EM-DAT sur les catastrophes naturelles dans le monde

Repo containing model training on high resolution flood response drone RGB drone imagery with pytorch and semantic segmentation models.

Repository for model of models development.

Tableau dashboard on natural disasters

Machine learning based natural disaster prediction for US counties

The objective of the project is to predict whether a particular tweet, of which the text (occasionally the keyword and the location as well) is provided, indicates a real disaster or not. We use various NLP techniques and classification models for this purpose and objectively compare these models by means of appropriate evaluation metric.

Jupyter Notebook showing my solutions to questions related to sample Category 5 Atlantic Hurricane Data. The data covers the years from 1928 to 2018.

A collection of weather, natural disaster, and US Census data processed and ranked to find the ideal home location for each individual's preferences.

A webapp that displays natural disasters on an interactive map. Built with Mapbox and LeafletJS.

A Django application to archive real-time earthquake notifications from the USGS's Advanced National Seismic System

🌋 Project for Morocco Solidarity Hackathon 🤝

Graduate deep learning course projects: Physics-informed neural networks for simulating physical systems and CNN-based wildfire prediction models.

Exploring deaths by natural disasters, and possible relations to climate change.

Modular structure that feeds on instant data, warns about natural disasters and conveys what needs to be done

Data visualization of death toll by natural disasters - written in Python3 using tkinter (GUI) and matplotlib (Visualization) .