experimentation

Open Source Feature Flagging and A/B Testing Platform

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.

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

Train to 94% on CIFAR-10 in less than 10 seconds on a single A100, the current world record. Or ~95.77% in ~188 seconds.

A 100% open-source feature flags management platform

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.

Track, version, compare and review your data and models.

🧪 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.

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

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 Fog Computing Emulation Framework

Experiments conducted for NaNoGenMo 2014