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Time Series Analysis
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Investigating Seasonality in a Time Series: A Mystery in Three Parts
Recently, I was asked to determine the extent to which seasonality influenced a particular time series. No problem, right? The statsmodels Python package has a seasonal_decompose function that seemed pretty […]
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Time Series Analysis: When “Good Enough” is Good Enough
Anomaly detection and time series forecasting are valuable in monitoring the financial and technical health of an organization. Proper modeling of time series requires accounting for periodic fluctuation; malicious users; data irregularity, saturation or scarcity; sudden peaks and drops. To account for these parameters, the modeler needs to select the proper model family, optimize the…
Data for Breakfast 