There are 1 repository under abtesting topic.
Open Source Feature Flagging and A/B Testing Platform
FeatureProbe is an open source feature management service. 开源的高效可视化『特性』管理平台,提供特性开关、灰度发布、AB实验全功能。
SwitchFeat is an open source and self-hosted feature flags and A/B testing framework written in Nodejs, Typescript and React.
I'm often asked, "How can I get into Product Management", so I wanted to share a list of resources to help you pivot!
A Cloudflare worker script used to enable a/b testing, canary releasing, gatekeeping, and SEO a/b/n testing.
Leanplum's integrated solution delivers meaningful engagement across messaging and the in-app experience.
A/B cookie testing tool for @Laravel
Solutions on Practical Data Science Specialization on Coursera (offered by deeplearning.ai)
Leanplum's integrated solution delivers meaningful engagement across messaging and the in-app experience.
Android library for displaying data based on JSON configuration fetched from server. With this library, you can kiss goodbye to string.xml, dimen.xml, arrays.xml. Keep all your string/integer/array config in one file. The library will automatically fetch the data from the url you provide.
Python notebooks for demonstrating various ideas, APIs, libraries.
toggler is a feature flag service to decouple deployment, feature enrollment and experiments
Unleash SDK for Next.js
A/B Testing Package for Neos
🏛️ Parameterized Build for React Native
An open-source feature flagging and experimentation platform that makes it simple to alter features and execute A/B testing.
AB Testing
A demo Android App to help Adhoc users to understand Adhoc Optimization services.
Apache Spark based framework for analysis A/B experiments
Growth Hacking knowledge system(黑客增长知识体系).
Leanplum's integrated solution delivers meaningful engagement across messaging and the in-app experience.
Simple React AB test component
Wrapper for providing optimizely-sdk server side experience in cached config way
Vamp Kubist is a management layer for Istio on Kubernetes
This project focuses on fundamental steps to set up an A/B test experiment, alongside some statistical analysis in Python.