WiDS Datathon 2020 on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative.

Using data within first 24 hours of intensive care to develop a machine learning model that could improve the current patient survival probability prediction system (apache_4a) and is more generalized to patients outside of the US

Predicting Diabetes Mellitus in ICU patients with data from the patient's first 24 hours.

This repository encompasses my submission for the WIDS (Women In Data Science) Challenge for 2018, held in Jan-Mar'18. It was an invite only competition based on InterMedia Survey Institute, a grant recipient of the Bill & Melinda Gates foundation in their Financial Services for the Poor program. Participants were required to predict gender base…

WiDS Datathon 2023 Contest 13th place WiDS Global and 1st place WiDS Hanoi solution by UET 杨蓉 Team (Binh Nguyen Thai, Duc Tran Van, Duong Tran Thuy, Dung Tran Thuy)

The dataset was created in collaboration with Climate Change AI (CCAI). Participants will submit forecasts of temperature and precipitation for one year, competing against the other teams as well as official forecasts from NOAA.

Predicting the presence of an oil palm plantation in an image

combination of EvalML with Rapids for the WiDS 2021 competition

Diabetes melitus adalah penyakit kronis yang terjadi ketika pankreas tidak dapat menghasilkan hormon yang mengatur gula darah (insulin) dengan cukup, atau ketika tubuh tidak dapat menggunakan insulin yang dihasilkannya. Prevalensi diabetes meningkat lebih cepat di negara berpenghasilan menengah dan rendah. Diperkirakan 1,6 juta kematian akibat d…

Women in Data Science(WiDS) Datathon 2021

Data Science practice for the WiDS 2022 Datathon

Use ML to predict gender from sparse data