There are 6 repositories under experimentation topic.
Open Source Feature Flagging and A/B Testing Platform
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.
This repo is for experimentation and exploring new ideas that may or may not make it into the main corefx repo.
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.
GO Feature Flag is a simple, complete and lightweight self-hosted feature flag solution 100% Open Source. 🎛️
Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Feature flags, experiments, and remote config management with version control
Open-source Python library for statistical analysis of randomised control trials (A/B tests)
Deep-Learning Model Exploration and Development for NLP
LLMOps with Prompt Flow is a "LLMOps 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.
PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more
🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.
Official Omnitool repository
🧪 Source-controlled split testing stack for building, launching and analysing A/B tests.
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.
Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.
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
Open Source version of SigOpt API, performing hyperparameter optimization and visualization
Transparent, robust and trustworthy A/B experimentation for Shopping feeds.
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Various eBPF programs for tracing network connections
A Fog Computing Emulation Framework
Unleash SDK for Next.js
Learning happens in the lab, not the lecture hall. This repo contains various different coding and technical lab experiments, exercises, and explorations. I refer to these during Beginner Boost a lot.
Experiments conducted for NaNoGenMo 2014
Official PostHog Node library
Official PostHog Go library