Predicting Air Pollution in Madrid: The Process
summary
Describes building predictive models for NO2 air pollution in Madrid using Python: collecting open data, selecting optimal variables, and iteratively creating models while applying agile data-science methodology. The goal is to anticipate high-pollution days so traffic-restriction protocols—currently decided day-to-day—can be planned in advance.
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chapters (7)
- 0:00Start
- 1:10Pollution data
- 4:59Prediction process
- 5:58Protocol rules
- 7:14Base ARIMA models
- 15:42Variable transformation: PCA
- 17:56Models with meteorology PCA
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