COVID-19 AI Data Analysis is a Peter Moss COVID-19 AI Research Project Artificial Intelligence & Data Analysis research & development project.
This repository will provide several projects created by our data scientists. Projects will include installation scripts, documentation and code for AI algorithms built for understanding COVID-19.
The Peter Moss COVID-19 AI Research Project is a Peter Moss Leukemia AI Research project. Our goal is to keep our research and technology open-source and free.
Below you will find a list of the current COVID-19 AI Data Analysis Projects.
| ID | Project | Description | Author |
|---|---|---|---|
| 1 | Covid 19 cases World Wide Analysis | Covid 19 cases World Wide Analysis. A continuation of COVID-2020 - a data scientist perspective. The original research showed that based on a population of 20,000,000 - 60,000,00, it will take roughly 1 year for the COVID-19 virus to curve off. - Original research referenced in: Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network by Kathakali Biswas, Abdul Khaleque, and Parongama Sen - Leukemia AI Research Article: COVID 2020 — A data scientist perspective |
Dr Amita Kapoor |
The Peter Moss COVID-19 AI Research Project encourages, and welcomes, code contributions, bug fixes and enhancements from the Github.
Please read the CONTRIBUTING document for a full guide to forking our repositories and submitting your pull requests. You will also find information about our code of conduct on this page.
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Adam Milton-Barker - Asociacion De Investigation En Inteligencia Artificial Para La Leucemia Peter Moss President & Lead Developer, Sabadell, Spain
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Dr Amita Kapoor, Delhi, India
We use SemVer for versioning. For the versions available, see Releases.
This project is licensed under the MIT License - see the LICENSE file for details.
We use the repo issues to track bugs and general requests related to using this project. See CONTRIBUTING for more info on how to submit bugs, feature requests and proposals.