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TimeGPT, Nixtla & Forecasting with Max Mergenthaler #53

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Innovations in Time Series Forecasting

This chapter explores groundbreaking features of a time series forecasting library and reflects on the impact of a pivotal research paper in the field. It discusses the evolving role of data scientists, emphasizing intelligent question formulation over algorithm implementation, while also considering the practical benefits of foundational models. Furthermore, it highlights the importance of clearly defining problems and adapting forecasting techniques to optimize specific utility functions in organizational contexts.

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