[WIP] Get smart insights, alerts & warnings about predicted natural disasters and take precautions before they arrive to keep family, friends & yourself safe.
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Updated
Oct 21, 2018 - JavaScript
[WIP] Get smart insights, alerts & warnings about predicted natural disasters and take precautions before they arrive to keep family, friends & yourself safe.
The PyDisaster project uses a master function that extracts GPS location and EXIF data from photos submitted to our Flask application platform, and opens a Google Maps search of the location. This project is geared towards helping FEMA conduct damage assessments in areas effected by natural disasters.
ResQ is a socially responsible Flutter Application. It assists the flood rescue operations.
Prediction of market premiums for property damage and business interruption insurance products. Added natural hazard data and stacked 3 best models as the final model.
Student research paper on precaution and prevention of natural disasters
Messiah: The Mighty Son Of God Is Here To Help You Through Times Of Calamity
It contains codes and documentations within the scope of the Special Topics in Remote Sensing course
Repository to preview, describe, and link to Tableau dashboard.
Exploring deaths by natural disasters, and possible relations to climate change.
Using Observable to make data visualizations
Registro de desaparecidos, proyecto que es una solución a los desastres naturales en Bolivia, es un sistema que trabaja persistencia con archivos, estructura de datos y programación orientada a objetos. Además, contiene una interfaz gráfica para interactuar con el registro el cual está hecho en JavaFx
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 Google Trends Sentiment Analysis integrated with FEMA emergency declarations data. I attempt to correlate isolated natural disasters with a change in search patterns for climate change. Emphasis on FL hurricanes and CA wildfires over the past 5 years.
Web scrape data on numerous biological hazards from numerous sources (EMDAT, IDMC, IFRC, DesInventar)
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.
Machine learning based natural disaster prediction for US counties
Data visualization of death toll by natural disasters - written in Python3 using tkinter (GUI) and matplotlib (Visualization) .
Tableau dashboard on natural disasters
Jupyter notebooks and web app that uses statistical analysis to prove climate change is real!
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