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DEEP LEARNING

Training Dynamics

Compare optimizer trajectories on loss landscapes, experiment with learning rate schedules — cosine, step, exponential — and measure batch size effects on convergence.

OptimizersLR ScheduleBatch Effects
OPEN INTERACTIVE LAB ↗

What you'll explore

  • ✓Training dynamics
  • ✓Learning rate schedule
  • ✓Optimizer comparison
  • ✓Loss landscape
  • ✓Batch size
  • ✓Training convergence

About this lab

Compare optimizer trajectories on loss landscapes, experiment with learning rate schedules — cosine, step, exponential — and measure batch size effects on convergence. This simulation runs entirely in your browser — no installation, no account required, no data uploaded.

Part of the Deep Learning Labs track — 8 labs covering the full curriculum.

PLATFORM FEATURES
✓ Runs 100% in browser — no server, no installs
✓ Adjustable parameters with real-time output
✓ Privacy-first: zero data collection or uploads
✓ Blockchain-verifiable experiment logs on Polygon
✓ Free to use — open to everyone