A Practical Approach to Timeseries Forecasting Using Python - RVT Models

The video tutorial explains time series decomposition, focusing on its components: level, trend, seasonality, and noise. It discusses how these components can be modeled using additive or multiplicative approaches. Additive models are linear with constant frequency and amplitude, while multiplicative models are non-linear with variable frequency and amplitude. The tutorial also highlights the importance of understanding these components for effective time series analysis and introduces automatic decomposition methods.

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