- Implementation of various baseline algorithms (Linear Regression, Vector Auto-Regression, LightGBM and Random Forests) to compare multi-step ahead forecasts of air quality with DCRNN as part of the paper "Exploiting spatiotemporal patterns for accurate air quality forecasting using Deep Learning".
- Data set includes information of monitoring stations in Los Angeles
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Build an accurate air quality forecasting model
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