Helloworld2345567/Google_TiDE_implementation
An implementation of (Google）Long-term Time Series Forecasting with TiDE: Time-series Dense Encoder
This project helps data scientists and machine learning engineers accurately predict future values in long-term time series data. It takes historical time series observations, along with static and dynamic contextual information (like holidays or time of day), and outputs forecasts for future time steps. This is useful for anyone needing efficient and robust long-term predictions from complex time-dependent datasets.
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Use this if you need to make long-term forecasts for multiple independent time series efficiently, leveraging both historical data and known contextual factors.
Not ideal if your primary goal is to achieve state-of-the-art accuracy at the expense of computational efficiency, or if your time series lacks relevant static or dynamic covariates.
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Last pushed
Jun 15, 2023
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