nbeats

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

Time Series prediction using Nbeats

Forecast Carbon Emissions with Time-Series data. This repository contains 2x Jupyter Notebooks that predict Carbon Emissions in the United States using Neural Basis Expansion Analysis for Time series (NBeats). The second notebook has an extra pre-processing step of data been scaled and inverse-transformed before final results.

A bitcoin price forecaster utilizing an ensemble of autoregressive, N-BEATS, LSTM and layer normalized models, trained on various loss functions.