A Practical Approach to Timeseries Forecasting Using Python - SARIMA in Python

The video tutorial covers the setup and application of the Cerimax model, a variant of ARIMA that includes exogenous variables. It explains how to import necessary modules, specify model orders, and fit the model to data. The tutorial also demonstrates forecasting with Cerimax, adjusting model parameters for better performance, and introduces the concept of making future predictions using data frames.

What are the four components mentioned in relation to the ARIMA model?

How can one improve the performance of the Cerimax model?

What is the purpose of using the auto ARIMA method?