The text discusses a time series analysis of the popularity of the search term “pumpkin spice” in the USA. The author explores different modeling techniques, such as SARIMA and ETS, to predict the seasonal patterns in the data. They compare the performance of these models against a naive model using last year’s data. The final ETS model outperforms the naive model and provides better predictions. The author also discusses future work, including automating the modeling process and exploring correlations with other data sources.
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Pumpkin Spice Time Series Analysis
- Towards Data Science – Medium
- Twitter – @itinaicom
