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The Architecture Used by Uber to Backtest Time Series Models at Scale
This architecture has been powering time series forecasting models at Uber for the last few years.
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Time-series forecasting is a key component of Uber’s machine learning architecture. Across its several properties, Uber runs thousands of time-series forecast models across diverse areas such as ride planning or budget management. Ensuring the accuracy of those forecast models is far from being an easy endeavor. The number of models and the scale of computation makes Uber’s environment relatively impractical for most backtesting frameworks. The backtesting frameworks such as Omphalos that Uber has built previously have proven to be…
