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The goal of this project is to help people on the front-line fighting COVID-19 find the most relevant research papers to better understand key pain-points and apply these findings into their plans and operations in addressing the pandemic.
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ak0123/scibertweb2
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#.. as well as Tutorial: Deploying a machine learning model to the webhttps://blog.cambridgespark.com/deploying-a-machine-learning-model-to-the-web-725688b851c7
The goal of this project is to help people on the front-line fighting COVID-19 find the most relevant research papers to better understand key pain-points and apply these findings into their plans and operations in addressing the pandemic.
The main issue is that more papers are published than there are qualified people to refind and leverage the knowledge.
This project can help to simplify the search process and bring the most relevant search results to eye-level for doctors, virologists, and other contributors mitigating the pandemic.
This project was forked from Issac MG's SciBERT Embeddings Analysishttps://www.kaggle.com/isaacmg/scibert-embeddings
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The goal of this project is to help people on the front-line fighting COVID-19 find the most relevant research papers to better understand key pain-points and apply these findings into their plans and operations in addressing the pandemic.
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