Open Source Feature Flags, Experimentation, and Product Analytics

UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.

Reactive Flux built with ImmutableJS data structures. Framework agnostic.

GO Feature Flag is a simple, complete and lightweight self-hosted feature flag solution 100% Open Source. 🎛️

Enterprise-grade feature flag platform that you can self-host. Get started - free.

Shadow is a discrete-event network simulator that directly executes real application code, enabling you to simulate distributed systems with thousands of network-connected processes in realistic and scalable private network experiments using your laptop, desktop, or server running Linux.

This repo is for experimentation and exploring new ideas that may or may not make it into the main corefx repo.

Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)

Feature flags, experiments, and remote config management with version control

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Official Omnitool repository

GenAIOps with Prompt Flow is a "GenAIOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.

Open-source Python library for statistical analysis of randomised control trials (A/B tests)

Deep-Learning Model Exploration and Development for NLP

PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more

JustTweak is a feature flagging framework for iOS apps.

🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.

RapidFire AI: Rapid AI Customization from RAG to Fine-Tuning

React SDK for Optimizely Feature Experimentation and Optimizely Full Stack (legacy).

JavaScript SDK for Optimizely Feature Experimentation and Optimizely Full Stack (legacy).

🧪 Source-controlled split testing stack for building, launching and analysing A/B tests.

Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.

A hardware kit to experiment with inflatable and vacuum based soft robotics.

moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility.

Transparent, robust and trustworthy A/B experimentation for Shopping feeds.

Android SDK for Optimizely Feature Experimentation and Optimizely Full Stack (legacy).

Official PostHog Go library

Ascend project

A list of self curated blogposts, videos and exercises on various technologies that I find interesting

A cloud-agnostic ML Platform that will enable Data Scientists to run multiple experiments, perform hyper parameter optimization, evaluate results and serve models (batch/realtime) while still maintaining a uniform development UX across cloud environments