Published inTowards Data ScienceHow Reliable Are Your Time Series Forecasts, Really?How cross-validation, visualisation, and statistical hypothesis testing combine to reveal the optimal forecasting horizonApr 57Apr 57
Published inPython in Plain EnglishTime series residuals: gold in them thar hillsHow model crumbs provide more insight than you might thinkMar 151Mar 151
Published inTowards Data ScienceFalse Prophet: Lightning Strikes TwiceInsights from incorporating external weather data into a time series regression inspired by Meta’s ProphetMar 11Mar 11
Published inTowards Data ScienceHybrid Models for Time Series RegressionUsing multiple model forms to capture and forecast the components of complex time seriesJan 131Jan 131
Published inTowards Data ScienceFalse Prophet: Comparing a Regression Model to Meta’s ProphetCan my Frankenstein of a time series regression model — inspired by Prophet — compete with the real deal?Nov 25, 20231Nov 25, 20231
Published inTowards Data ScienceFalse Prophet: a Homemade Time Series Regression ModelBorrowing ideas from Meta’s Prophet to build a powerful time series regression modelOct 31, 20235Oct 31, 20235
Published inTowards Data ScienceFalse Prophet: Feature Engineering for a Homemade Time Series RegressionBuilding on ideas from Meta’s Prophet package to create powerful features for time series machine learning modelsOct 13, 20232Oct 13, 20232
Published inPython in Plain EnglishOn Times Series Cross-ValidationMaximising the utility of your time series data with smart subdivision.Jun 26, 2023Jun 26, 2023
Published inTowards AILet’s Do: Time Series DecompositionA guide to effectively breaking a time series into its constituent partsJun 17, 20231Jun 17, 20231