We all know it by now: the novel coronavirus, resulting in COVID-19, is spreading across the globe. In haste, governments are taking unprecedented measures such as total lockdown (France and Italy) and controlled spread (Netherlands). In doing so, they attempt to reduce the impact of the virus on the countries' health systems, awaiting a vaccine to be developed and considered safe.
However, we as data science, data engineering and machine learning communities might just be able to help fight the virus - especially in times where other work might be getting less.
The CORD-19 challenge is a Kaggle challenge launched by the Allen Institute for AI in partnership with the Chan Zuckerberg Initiative, Georgetown University’s Center for Security and Emerging Technology, Microsoft Research, and the National Library of Medicine - National Institutes of Health, in coordination with The White House Office of Science and Technology Policy.
COVID-19 picture: Miguel Á. Padriñán, Pexels.com
It comes with a dataset of more than 29.000 scholarly articles:
In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 29,000 scholarly articles, including over 13,000 with full text, about COVID-19, SARS-CoV-2, and related coronaviruses. This freely available dataset is provided to the global research community to apply recent advances in natural language processing and other AI techniques to generate new insights in support of the ongoing fight against this infectious disease. There is a growing urgency for these approaches because of the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up.
There is a wide range of tasks available, each with $1000 euro in prizes for the winner, sponsored by Kaggle:
If you have some spare time, it might definitely be worth a look - and perhaps, even a try. Click here to go to the challenge.
Learn how large language models and other foundation models are working and how you can train open source ones yourself.
Keras is a high-level API for TensorFlow. It is one of the most popular deep learning frameworks.
Read about the fundamentals of machine learning, deep learning and artificial intelligence.
To get in touch with me, please connect with me on LinkedIn. Make sure to write me a message saying hi!
The content on this website is written for educational purposes. In writing the articles, I have attempted to be as correct and precise as possible. Should you find any errors, please let me know by creating an issue or pull request in this GitHub repository.
All text on this website written by me is copyrighted and may not be used without prior permission. Creating citations using content from this website is allowed if a reference is added, including an URL reference to the referenced article.
If you have any questions or remarks, feel free to get in touch.
TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.
PyTorch, the PyTorch logo and any related marks are trademarks of The Linux Foundation.
Montserrat and Source Sans are fonts licensed under the SIL Open Font License version 1.1.
Mathjax is licensed under the Apache License, Version 2.0.