How to Forecast Time Series Data using any Supervised Learning Model

The article discusses the process of forecasting time series data by transforming it into a tabular format using open-source libraries. It shows how a multiclass classification model can outperform time series forecasting models and how AutoML can further improve accuracy. The dataset used is the PJM hourly energy consumption data, and the accuracy of the AutoML model is 89%.