Team Name | ParkinStrike (Katalyze Data) |
Track | Health care & Life Sciences |
Use Case | Machine learning including advanced feature engineering and deep learning techniques that classifies users whether or not they have Parkinson's disease, based on mouse cursor movements. The model or models deemed successful will be deployed as a SAS Viya REST API web service that can be used to score visitor's activity Deploying this model as a service and also using SAS Decision Connector with Power Apps as a client to the API will showcase the comprehensive functionality available in SAS Viya to operationalise analytics with a couple of clicks. |
Technology | Python, SAS Viya, SAS Decision Connector |
Region | EMEA |
Team lead | @tamasbo |
Team members | Jaan Nellis, Paul Burgess, Michael Walshe, Lucy Parkin, Barbara Mikulášová, Bob Kettlewell, Paul Shannon, Ian Amaranayake, Fraser Scott, Tamas Bosznay |
Social media handles | *all team members' social media links here* |
Is your team interested in participating in an interview? | Y |
Optional: Expand on your technology expertise | SAS, Python, R |
Jury Video:
Pitch Video:
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