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holt-winters

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Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models

  • Updated Dec 30, 2019
  • Jupyter Notebook

The repository provides an in-depth analysis and forecast of a time series dataset as an example and summarizes the mathematical concepts required to have a deeper understanding of Holt-Winter's model. It also contains the implementation and analysis to time series anomaly detection using brutlag algorithm.

  • Updated Jun 4, 2021
  • Jupyter Notebook

Forecast the Airlines Passengers. Prepare a document for each model explaining how many dummy variables you have created and RMSE value for each model. Finally which model you will use for Forecasting.

  • Updated Aug 27, 2022
  • Jupyter Notebook

With the help of a brand new KATS package, we can detect outliers, change points, and build very strong Time Series Analysis models. By inspecting this repository you can get a solid vision of KATS on real Covid-19 data of Azerbaijan.

  • Updated Jul 12, 2021
  • Jupyter Notebook

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