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Forecasting Impact
Forecasting Impact
49 episodes
1 week ago
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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Education
Business,
Non-Profit,
How To
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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 ...
Show more...
Education
Business,
Non-Profit,
How To
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Panel on Foundational Models with Azul Garza Ramírez and Mononito Goswami- Part 2
Forecasting Impact
45 minutes
1 year ago
Panel on Foundational Models with Azul Garza Ramírez and Mononito Goswami- Part 2
In this episode, hosts Mariana Menchero and Faranak Golestaneh explore the cutting-edge world of foundation models for time series forecasting with guests Azul Garza Ramírez, cofounder of Nixtla, and Mononito Goswami, one of the developers of MOMENT, a family of open-source foundation models for general-purpose time series analysis. The conversation delves into the backgrounds of these innovators and their journey into the realm of time series analysis and forecasting. The podcast explores th...
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 ...