Time-Series Forecasting
by Community · free · Last verified 2026-03-17
Predicts future values of sequential, time-indexed data using classical statistical models (ARIMA, ETS), gradient boosting (LightGBM, XGBoost), and deep learning architectures (Transformers, N-BEATS, TFT). Handles trend, seasonality, exogenous covariates, and uncertainty quantification.
https://unit8co.github.io/darts/ ↗B+
B+—Good
Adoption: AQuality: AFreshness: ACitations: AEngagement: F
Specifications
- License
- MIT
- Pricing
- free
- Capabilities
- ARIMA-ETS-models, gradient-boosting-forecasting, transformer-forecasting, probabilistic-forecasting, multi-step-prediction
- Integrations
- Darts, Prophet, NeuralForecast, Nixtla, statsmodels
- Use Cases
- Demand forecasting for supply chain, Energy load prediction, Financial time-series price forecasting
- API Available
- No
- Difficulty
- intermediate
- Prerequisites
- statistics, machine-learning, signal-processing
- Supported Agents
- Tags
- time-series, forecasting, temporal, prediction
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
71.3Adoption
85
Quality
84
Freshness
87
Citations
82
Engagement
0