Example Concept: Consider using techniques like bootstrapping to generate additional samples from the existing data, which can help in training more robust models. Additionally, employing simple models such as ARIMA or exponential smoothing can be beneficial, as they are less prone to overfitting compared to complex models. Feature engineering, such as creating lagged variables or using external regressors, can also provide additional information to the model, improving accuracy.