thinking bayes

Open Source

Data Science and Statistics Updated Feb 15, 2026

Overview

Thinking Bayes is a Python library that implements Bayesian analysis for data science applications. It provides tools for modeling and analyzing data using Bayesian methods. The project is based on a book on Bayesian analysis, providing a comprehensive framework for Bayesian modeling and computation.

Problem It Solves

Bayesian modeling and analysis of data

Target Audience: Data scientists and statisticians

Inputs

• data sets
• prior distributions
• likelihood functions

Outputs

• posterior distributions
• Bayes factors
• predictions

Example Workflow

1 data preparation
2 model specification
3 prior elicitation
4 likelihood computation
5 posterior inference
6 model evaluation

Sample System Prompt


              Use Thinking Bayes to analyze a dataset and estimate the posterior distribution of a parameter

Tools & Technologies

Matplotlib Scikit-learn

Alternatives

• PyMC3
• Stan
• scipy.stats

FAQs

Is this agent open-source?: Yes
Can this agent be self-hosted?: Yes
What skill level is required?: Intermediate