Team mission
Develop a domain agnostic deep learning for time series forecasting, classification, and anomaly detection framework and leverage it solve pressing problems in health, climate, agriculture, and other high impact humanitarian areas.
đź”— Project information
COVID-19 County Dashboard
đź“‹ Roadmap overview
As explained above we have two major focuses: (1) general repository enhancements that can be applied to any time series problem and (2) vertical impact focus areas that can aim to tackle a specific issue (e.g. COVID spread, flash flood prediction…).
🔍 Detailed quarterly roadmap
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Core Repository Focus Areas
Feature | Priority | Effort | Status | Notes |
---|---|---|---|---|
Adding new time series models/loss functions | MEDIUM | MEDIUM | IN PROGRESS | Leverage PyData Global Sprint |
Meta-data incorporation | HIGH | HIGH | IN PROGRESS | |
Model Interpretability | HIGH | MEDIUM | IN PROGRESS | |
Increasing test coverage | HIGH | MEDIUM | IN PROGRESS | Good to get 3rd party review of training loops. |
Documentation and tutorials | MEDIUM | MEDIUM | IN PROGRESS | |
Auto experimentation | LOW | HIGH | NOT STARTED | |
Cloud Provider Integration | MEDIUM | MEDIUM | IN PROGRESS |
Application/Impact Focus Areas
Feature | Priority | Effort | Status | Notes |
---|---|---|---|---|
COVID County Dashboard | HIGH | HIGH | IN PROGRESS | Link to Slideshow |
River flow dashboard | MEDIUM | HIGH | NOT STARTED | |
River flow open-source | MEDIUM | HIGH | IN PROGRESS | |
Research Focus Areas
Focus Area | Priority | Effort | Status | Notes |
---|---|---|---|---|
Incorporating meta-data in TS models | ||||
Transfer learning in time series application | ||||