Time Series for Predicting Air Quality (PM2.5/PM2) with analysis to show the PM2 levels and their changes with ACF and PACF plots that represent the average correlation between data points in time series and previous values of the series measured for different lag lengths
with a Baseline model to show the maximum MAE that a good model will reach it
The Evaluation of the model showed WFV predictions (Walk-forward predictions) and represented the predictions and actual data
- Pandas
- Matplotlib
- Sci-kit learn
- Stats Models