Scalable and user friendly neural 🧠 forecasting algorithms.
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Updated
Jul 11, 2024 - Python
Scalable and user friendly neural 🧠 forecasting algorithms.
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
A Full-Pipeline Automated Time Series (AutoTS) Analysis Toolkit.
Time-Series models for multivariate and multistep forecasting, regression, and classification
📈 toolset for time series forecasting
A bitcoin price forecaster utilizing an ensemble of autoregressive, N-BEATS, LSTM and layer normalized models, trained on various loss functions.
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