First place solution for Open Cities DrivenData challenge
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Updated
Mar 22, 2020 - Jupyter Notebook
First place solution for Open Cities DrivenData challenge
1st place solution of Team Epoch on the Kelp Wanted competition hosted on DrivenData.
Solution for N+1 fish, N+2 fish DrivenData competition (2nd place)
Estimating the extent of Giant Kelp Forests by segmenting Landsat imagery
Unreal Text Engine - Work in progress
This repository contains source code and pre-trained models for the 2nd place solution of the Overhead Geopose Challenge.
Solution for DengAI Competition by DrivenData (CS4642 Data Mining and Information Retrieval, CS4622 Machine Learning - assignments)
"Pump It Up: Data Mining the Water Table" competition from DrivenData. Análisis exploratorio, procesamiento de datos y modelado predictivo aplicados para clasificar el estado funcional de bombas de agua en Tanzania.
42nd (top 5%) place solution of On Cloud N: Cloud Cover Detection Challenge competition
Workings for my entry for the competition https://www.drivendata.org/competitions/57/nepal-earthquake/
Demo repo for DrivenData competition "Flu Shot Learning: Predict H1N1 and Seasonal Flu Vaccines" in R
Warm Up: Predict Blood Donations
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 7500+ competitors.
DengAI: Disease spread prediction(DrivenData Challenge)
Blood donation has been around for a long time. The first successful recorded transfusion was between two dogs in 1665, and the first medical use of human blood in a transfusion occurred in 1818. Even today, donated blood remains a critical resource during emergencies. More info on : https://www.drivendata.org/competitions/2/warm-up-predict-bloo…
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.
Predicting water pump status in Tanzania (functional / needs repair / non-functional) for the DrivenData Pump It Up competition. Random Forest → Stacking Ensemble pipeline with feature engineering, class imbalance strategies, and an AI-powered EDA agent built with LangGraph + LangChain.
Tomada de decisão e o planejamento estratégico na coleta e na análise de informações.
playing with https://www.drivendata.org and https://www.kaggle.com
DrivenData Challenge
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