Modern Approaches to Time Series Analysis

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Published:

Time series analysis is fundamental to many data science applications, from financial forecasting to climate modeling. This post explores contemporary approaches to analyzing temporal data, combining traditional statistical methods with modern machine learning techniques.

We’ll explore:

  • ARIMA and SARIMA models
  • Prophet framework by Facebook
  • Deep learning approaches (LSTM, Temporal CNN)
  • Feature engineering for time series
  • Handling seasonal patterns and trends

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