A feature-rich library for running Bayesian A/B tests for experiments and key metrics analysis
The simulation of Epsilon-Greedy and Thompson Sampling algorithms for Bayesian A/B Testing. The project shows how both algorithms find the optimal bandit and approximate the rewards of each bandit, given the true reward. Visualizations are done to demonstrate the learning process and convergence.
Production-Grade A/B Testing & Statistical Experimentation Simulator: Power Sizing, SRM Detection, Outlier Winsorization, CUPED Variance Reduction, Bayesian Decision Theory & mSPRT Sequential Testing.
Production-ready Bayesian & Frequentist A/B Testing framework with Monte Carlo simulation, interactive Streamlit dashboard, statistical decision engine, and live deployment.
Bayesian AB testing in python
Bayesian A/B testing pipeline on GCP - MovieLens 25M with closed-form Bayesian + multivariate CUPED + Cloud Run
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