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Erin Boyle, Head of Data Science, Myst AI
Myst AI has over three years of experience delivering highly accurate forecasts to organizations in clean power like climate-conscious load-serving entities, renewable power providers, and more. This talk will discuss some of the key ingredients we’ve identified as critical to delivering ongoing accuracy in our deployed load forecasting models. We’ll speak in particular to solutions to real-world data complexities: cross-validation in a domain where upstream forecasts are themselves critical features and historical data update over time, as well as ensembling approaches that solve unique challenges around data availability.