The solution creates two distinct forecasts from the data uploaded by the user:   **simple forecast**  and  **advanced forecast**. The following articles provide detailed information about the approach and forecasting methods used in each case as well as the  **performance evaluation**  method used to compare results.

## Summary

1. [Simple Forecast](article:37): To build the simple forecast and create new features to use in the regression model, this solution uses time series models to forecast future values over the next horizons per category.

2. [Advanced Forecast](article:38): This solution uses an Extra Random Tree regression model to forecast the next horizons.

3. [Performance Evaluation](article:39): To compare the performance between forecasting methods, the solution computes the Mean absolute percentage error (MAPE).




