:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.
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A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
🦉 Data Versioning and ML Experiments
Image augmentation for machine learning experiments.
Open-source feature management platform
WebRTC, WebRTC and WebRTC. Everything here is all about WebRTC!!
Tool for real-time visualization, monitoring and collaborative analysis of AI/ML experiments and live data. Supports Python, PyTorch/Torch, NumPy, TensorFlow/Keras https://visdom.dev
Playing Pokemon Red with Reinforcement Learning
Litmus helps SREs and developers practice chaos engineering in a Cloud-native way. Chaos experiments are published at the ChaosHub (https://hub.litmuschaos.io). Community notes is at https://hackmd.io/a4Zu_sH4TZGeih-xCimi3Q
An authoritative list of awesome devsecops tools with the help from community experiments and contributions.
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
GO Feature Flag is a simple, complete and lightweight self-hosted cloud native feature flag solution 100% Open Source — built on OpenFeature 🎛️
Hyperparameter Experiments with TensorFlow and Keras
learn code with tensorflow
2D, 3D & VR experiments and tutorials in Godot 3 & 4
A Database of Real Faults and an Experimental Infrastructure to Enable Controlled Experiments in Software Engineering Research
Examples and experiments around ML for upcoming Coding Train videos
Mostly experiments based on "Advances in financial machine learning" book
Draft-JS experiments with drag&drop, resizing, tooltips, WIP
Open PS5 firmware 14.10 research: Lua userland experiments, syscall and attack-surface analysis. Kernel read/write and a complete exploit are not demonstrated.
Code and data used to create the examples in "Evidence-based Software Engineering based on the publicly available data"
FOREST is a research agent for long-horizon science, where evidence gets lost, errors compound, and goals drift. It explores ideas, reads literature, forms hypotheses, runs real experiments, analyzes results, revises paths, and builds a full paper—all in an editable graph you can inspect, branch, redirect, with claims and figures linked to evidence
Code for all experiments.
WebGL Shader demos - GPU rendering shader experiments with procedural 3D scene generation using ray marching and distance field (also known as 'sphere tracing') rendering techniques.