In the notebook 2 of this section, why do we use the mean squared error (MSE) instead of the square root of MSE (RMSE)?
I felt it would be nice to have the mean absolute error (MAE) and MSE in the same scale.
It seems that by default sklearn returns the MSE and by passing squared=False we get RMSE.
model_error = mean_squared_error(target, inferred_body_mass, squared=False)