Data Science - Time Series Forecasting with Facebook Prophet in Python - Walk-Forward Validation

The video tutorial introduces walk forward validation as a suitable method for time series data, contrasting it with traditional train-test splits and K-fold cross validation, which are inadequate due to time dependencies. Walk forward validation involves incrementally training models with past data to predict future outcomes, reflecting real-world scenarios. The tutorial also discusses practical considerations, such as step sizes and data windowing, and highlights limitations of using Psykitlearn for time series validation.

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