MachineLearning

Investigating Multi-Layer Perceptrons, Convolutional Neural Networks, Regression Models, and Ensembl methods for prediction of disease progression, impact of geographical distribution, etc.

Sources of data:

• Johns Hopkins repo
• European Centre for Disease Prevention and Control
• Automated Data Collection: COVID-19/SARS-COV-2 Cases in EU by Country, State/Province/Local Authorities, and Date

Potential tools:

• Coronavirus Tracker API

(Side Note: There seems to be some overlap between this Task and the BioStatistics Task. It may be worth considering merging these two.)

Machine learing requires much computing resources, in many cases GPUs. Kubeflow, as a highly portable and cloud native platform, is designed for machine learning. Containerised workloads can easily be ported onto it.

Participants

• Fotis Psomopoulos
• David Yuan
• Elizabeth Pereira
• Lukas Heumos
• Yachee Gupta
• Simon Verheyen