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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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 ...
Mitchell O'Hara-Wild on open source forecasting and R
Forecasting Impact
47 minutes
1 year ago
Mitchell O'Hara-Wild on open source forecasting and R
In this episode, we had the privilege of hosting Mitchell O'Hara-Wild, data scientist and lead developer of the widely used and highly acclaimed forecasting packages, Fable and Feasts. Mitchell is a PhD candidate at Monash University, Australia. He shared insights on a wide range of topics, including his journey into data science and forecasting, the reasons behind the development of the popular Fable package, and his views on AI in forecasting. We also discussed Mitchell’s rese...
Forecasting Impact
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 ...
