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@Isaac Godfried - Project lead
Provide a central repository of the latest deep learning for time series techniques.
Allow data scientists and ML engineers to easily test many different models and slight architectural variations to address their specific business use case.
Enable researchers to easily experiment, develop, and test novel deep learning for time series architectures.
Facilitate the incorporation of many modalities of data to improve model performance.
Open source and benchmark time series datasets in health, climate, and agriculture.
Enable easy integration with cloud providers AWS, GCP, Azure.