Composable Forecasting Workflows
Erin discusses the innovative approach to creating flexible forecasting workflows that support a wide range of models and feature transformations. She highlights the challenges of integrating historical data in domains like electricity demand forecasting and the importance of making advanced data science techniques accessible to a broader audience. The platform aims to empower users, from those with limited data science backgrounds to experienced data scientists, by managing infrastructure and allowing them to focus on experimentation and optimization.In this clip
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Data Skeptic
Energy Forecasting Pipelines
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