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WorldHealthOrganization / app

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someshkar / covid19india-cluster

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Female placed as the default gender; Create a new gender representing missing info/third gender

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loCoder
loCoder commented Apr 2, 2020

Describe the bug
In the raw database, genders of some patients is missing, and the same is reflected in the cluster by displaying it as female. Also, it may not be possible for the crowd-sourced data to get gender of all the patients. Also, it gives wrong visualization inference, that more females are infected by the virus.

To Reproduce
Steps to reproduce the behavior:

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curiousily / Getting-Things-Done-with-Pytorch

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Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

nlp machine-learning tutorial computer-vision deep-learning time-series sentiment-analysis pytorch transformer lstm yolo face-recognition face-detection object-detection transfer-learning bert anomaly-detection time-series-forecasting coronavirus time-series-anomaly-detection
  • Updated Jan 23, 2021
  • Jupyter Notebook

MinCiencia / Datos-COVID19

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