How niravrvaghasiya/playtolearnml works
GameML is a browser-based machine-learning learning product: players choose a game, manipulate an algorithm through visual or code controls, and receive live metrics and explanations. The README documents all 14 games, six subject categories, a concept library, local progression, and optional Supabase progression support. The tree and sampled source support the shared engine, code execution, TensorFlow.js lifecycle, and representative game logic; unsampled game wiring is not expanded into speculative call chains.
Main entry points: registry.ts Game registry · GameShell.tsx Game shell · GameMount.tsx Game mount · progression.ts Progression engine
Components 18
Web experience
- Game routes
src/app/play/[slug]/page.tsx - Concept library
src/app/concepts - Game mount
src/games/GameMount.tsx - Game registry
src/games/registry.ts - Shared UI
src/components/index.ts
Shared runtime
- Game shell
src/engine/GameShell.tsx - Code lane
src/engine/useCodeLane.ts - Model lifecycle
src/engine/useModel.ts
Game curriculum
- Data preparation
src/games/data-detox - Supervised learning
src/games/sort-it-arcade - Neural networks
src/games/neuron-forge - Optimization tuning
src/games/gradient-descent-skier - Unsupervised learning
src/games/k-means-territory-wars - Reinforcement learning
src/games/agent-academy
Learning progress
- Progression engine
src/engine/progression.ts - Browser progress
src/engine/progression.ts
Other components
- Learner
- Supabase
Connections 17
- Learner → Game routes: chooses game
- Game routes → Game mount: loads game
- Game mount → Game registry: selects entry
- Learner → Concept library: reads concepts
- Game mount → Game shell: runs session
- Game shell → Shared UI: renders controls
- Game shell → Code lane: offers code lane
- Game shell → Progression engine: records results
- Code lane → Model lifecycle: runs ML code
- Game registry → Data preparation: exposes games
- Game registry → Supervised learning: exposes games
- Game registry → Neural networks: exposes games
- Game registry → Optimization tuning: exposes games
- Game registry → Unsupervised learning: exposes games
- Game registry → Reinforcement learning: exposes games
- Progression engine → Browser progress: saves locally
- Progression engine → Supabase: syncs progress