sklearn-bayes
A Python package providing Bayesian machine learning algorithms with a scikit-learn compatible API.
What is sklearn-bayes?
sklearn-bayes is a Python package that implements Bayesian machine learning algorithms with a scikit-learn compatible API. It provides probabilistic alternatives to traditional machine learning methods, allowing users to incorporate uncertainty estimates and Bayesian inference into their models while using familiar scikit-learn interfaces.
Data scientists and machine learning practitioners who want to use Bayesian methods but prefer the consistent API design of scikit-learn. It's particularly useful for those transitioning from frequentist to Bayesian approaches in their ML workflows.
Developers choose sklearn-bayes because it eliminates the learning curve associated with new Bayesian libraries by providing drop-in replacements for scikit-learn estimators. It offers production-ready implementations of advanced Bayesian algorithms with the same fit/predict interface that Python ML practitioners already know.
Overview
Python package for Bayesian Machine Learning with scikit-learn API
Use Cases
Best For
- Implementing sparse Bayesian regression with Relevance Vector Machines
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