
Marco Peixeiro discusses the importance of explainability in time series forecasting and how it builds trust in complex models.
In this episode of Forecasting Impact, hosts Mahdi Abolghasemi and Mariana Menchero speak with Marco Peixeiro, applied data scientist at Nixtla, about the growing importance of explainability in time series forecasting. Marco shares how his work bridges research and practice, from developing deep learning models in NeuralForecast to writing educational resources that make complex forecasting concepts accessible to all. We discuss how explainability builds trust in complex models, the role of ...
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