1 Introduction
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Time series problems are very important in the industry and academia. Many commercial applications use time series data, such as stock market analysis and predicting consumer behavior in retail. Time series data is used extensively in weather forecasting, stock market prediction, demand forecasting, and many more applications.
The landscape in machine learning for time series has been changing and many different libraries and algorithms are out there to deal with time series. Some popular methods for time series include ARIMA, LSTM, Prophet, and SARIMA. ...
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