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In this section, we will estimate airline passengers using time series methods.
In this section, we will examine the Exponential Smoothing Methods in time series analysis.
Time Series Analysis Intro
Airline Passengers Forecasting
Content: Unsupervised ML, Time Series analysis, Exponential Smoothing, Single Exponential smoothing, Holt Model, Holt Winter model, ARIMA model
One of the most important tasks for any retail store company is to analyze the performance of its stores. The main challenge faced by any retail store is predicting in advance the sales and inventory required at each store to avoid overstocking and under-stocking. This helps the business to provide the best customer experience and avoid getting into losses, thus ensuring the store is sustainable for operation.
This series covers SES, DES and TES techniques we use in time series.
In this section, there is a discussion of the Exponential Smoothing Method in time series analysis.