skbayes

Bayesian Machine Learning with scikit-learn API

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is skbayes?

Python package for Bayesian Machine Learning that integrates seamlessly with the popular scikit-learn framework, offering a familiar interface while enabling probabilistic modeling.

Key differentiator

skbayes stands out by providing Bayesian machine learning capabilities within the well-known scikit-learn framework, making it accessible to a wide range of users without sacrificing advanced statistical methods.

Capability profile

Strength Radar

Seamless integra…Supports Bayesia…Provides probabi…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Seamless integration with scikit-learn API for ease of use

Supports Bayesian linear regression and Gaussian processes

Provides probabilistic predictions alongside model parameters

Fit analysis

Who is it for?

✓ Best for

Teams looking to integrate Bayesian methods into their ML pipelines using familiar APIs

Developers who need probabilistic predictions for decision-making processes

✕ Not a fit for

Projects requiring real-time inference with minimal latency

Applications where deterministic models are preferred over probabilistic ones

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with skbayes

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →