Implemented a machine learning model to predict the likelihood of individuals receiving H1N1 and seasonal flu vaccinations and ranked 20 in the Driven Data out of 6500+ competitors.
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Sep 24, 2024 - Jupyter Notebook
Implemented a machine learning model to predict the likelihood of individuals receiving H1N1 and seasonal flu vaccinations and ranked 20 in the Driven Data out of 6500+ competitors.
1st place solution of Team Epoch on the Kelp Wanted competition hosted on DrivenData.
Estimating the extent of Giant Kelp Forests by segmenting Landsat imagery
This is my repository for the Pale Blue Dot: Visualization Challenge
Mini Competition: Richter's Predictor
Exploratory data analysis and model preparation for DrivenData contest: PumpItUp!
My explorations, visualizations, and models from the DrivenData.co DengAI competition
Classify Pumps into “functional”, “functional needs repair” or “Non-functional” categories based on a number of variables about what kind of pump is operating, when it was installed, and how it is managed, etc.
A data analysis as part of a challenge on drivendata.org which aims to find some correlations and predict how likely individuals are to receive their H1N1 and seasonal flu vaccines.
This repository contains source code and pre-trained models for the 2nd place solution of the Overhead Geopose Challenge.
Tomada de decisão e o planejamento estratégico na coleta e na análise de informações.
Deep Chimpact: Depth Estimation for Wildlife Conservation Solution by Team RTX 4090 (1st place)
42nd (top 5%) place solution of On Cloud N: Cloud Cover Detection Challenge competition
Segmentation of clouds using satellite imagery
Data files and code for the Driven Data project on predicting which water pumps need repair for about 60K water pumps in Tanzania. See the URL https://www.drivendata.org/competitions/7/pump-it-up-data-mining-the-water-table/
Code for the "STAC Overflow" competition on DrivenData.
Based on aspects of building location and construction, was made a MLP (MuiltiLbal Perceptron) to predict the level of damage to buildings caused by the 2015 Gorkha earthquake in Nepal.
Demo repo for DrivenData competition "Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines" in R
Workings for my entry for the competition https://www.drivendata.org/competitions/57/nepal-earthquake/
Richter's Predictor: Modeling Earthquake Damage Challenge 0.7521 Scored Solution
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