> ML_LIBRARY // PROPHET_v1.0
Prophet
Meta Open Source — Meta's automated forecasting tool optimized for business metrics and human-interpretable seasonality.
time-series-forecastingv1.1.5MITqualified
Model Training
Accelerators:
CPU
Distributed Training:No
Model Inference
Inference Accelerators:
CPU
Deployment Targets:server
What It Does
- +Decomposable time series model combining trend, multiple seasonalities (daily, weekly, yearly), and holidays
- +Robust handling of missing data, outliers, and historical structural trend shifts
- +Intuitive parameters understandable by non-data-scientist business stakeholders
- +Built-in cross-validation and performance metric evaluation
What It Does Not Do
- -Model complex non-linear auto-regressive dependencies across high frequencies (sub-minute data)
- -Compute cross-series multivariate covariances natively
- -Run directly on GPU hardware accelerators
>Suitable Work Types
- Corporate quarterly revenue and sales planning
- E-commerce website traffic projections accounting for Black Friday and holidays
- Capacity planning for cloud infrastructure over months and years
>Unsuitable Work Types
- Millisecond high-frequency algorithmic sensor telemetry
- Hierarchical retail SKU forecasting with millions of interrelated items (use StatsForecast/Nixtla)
Data Residency Implications
Runs entirely on internal server nodes. Zero telemetry.
Security Considerations
MIT license with permissive commercial rights. CmdStan backend builds native C++ code.
Operational Profile & Known Limitations
Maturity:mature
Learning Curve:low
Ops Complexity:low
Cost Tier:free-oss
> Known Limitations:
- Can overfit to recent seasonal noise or fail to capture complex autoregressive lags without extensive manual regressor engineering.
Associated Incident Patterns (Incidentpedia)
Enforce safeguards and monitoring to guard against these documented real-world failure modes:
> Primary Evidence & Benchmark Citations
Prophet Documentationofficial-docs • >=1.1.0, <=1.1.x
2026-09-25HIGH