Free
Free
Open-source framework installable via pip with public GitHub resources linked from the site.
- Access
- Open-source framework installable via pip with public GitHub resources linked from the site.
NeuralProphet
● Identity checkedResearch · Vendor site 2026-10-04
NeuralProphet is an open-source PyTorch time-series forecasting framework that blends classical decomposition ideas with neural networks for explainable forecasts at scale. The homepage provides pip-install guidance and sample Python code for fitting and predicting daily series data.
- Category
- Research
- Free access
- Open-source framework installable via pip with public GitHub resources linked from the site.
- API access
- Not confirmed
Is NeuralProphet right for you?
A good fit for
Data scientists and engineers who want a Python-native forecasting library bridging traditional and deep learning approaches.
Before you choose
Users run and host their own Python environments; the project site does not provide a managed forecasting SaaS.
Neural time-series library
NeuralProphet presents a lightweight Python API for training and predicting time series with neural components and links to deeper docs on GitHub.
What it can do
Features & capabilities
Unknown is different from unavailable. Each fact carries its own evidence.
| Capability | Value | Evidence | Checked |
|---|---|---|---|
| PyTorch foundation | Homepage states NeuralProphet is based on PyTorch and installable using pip. | Facts sourced | 2026-10-04 |
| Explainable forecasting | Site tagline highlights explainable forecasting at scale between traditional and deep learning methods. | Facts sourced | 2026-10-04 |
| Quickstart code | Landing page shows sample fit and predict calls using pandas data with daily frequency. | Facts sourced | 2026-10-04 |
Understand the total cost
NeuralProphet pricing & plans
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Explore toolThe practical questions
Frequently asked questions
What is NeuralProphet used for?
NeuralProphet is an open-source PyTorch time-series forecasting framework that blends classical decomposition ideas with neural networks for explainable forecasts at scale. The homepage provides pip-install guidance and sample Python code for fitting and predicting daily series data.
Does NeuralProphet have a free plan?
Open-source framework installable via pip with public GitHub resources linked from the site.. This record lists ongoing free access; check the plan limits before starting.
How much does NeuralProphet cost?
No paid monthly price is listed; this record treats the product as free to start. See the plan cards for entitlements, billing commitments and seat minimums.
Can I use NeuralProphet through an API?
Not confirmed. API access and subscription access may have different terms; consult the linked sources.
What should I check before choosing it?
Users run and host their own Python environments; the project site does not provide a managed forecasting SaaS.
Price history
No retained pricing changes yet. A current price alone does not establish a historical trend.
How this profile is supported
Identity and profile
Reviewed vendor source
Read original source ↗Facts apply to the named version and check date. Send a sourced correction if something changed.