As time -series feature extraction have played an important role in analyzing trends, predicting future events and anomalies, it becomes important for data scientists to get acquainted with different libraries. One such library is tsfeatures
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time series
An Insight of Time Series Traditional vs Deep Learning Technique Motivation There are most commonly five types of traditional time series models, which includes the following. They have played an important role in different industry for time-series forecasting. Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA), Autoregressive Integrated Moving Average (ARIMA), and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. AR models have been known to express the current value of the time series linearly. […]
