Weights & Biases

Weights & Biases logs every detail of your ML experiments (parameters, metrics, outputs, hardware usage) and gives you dashboards to compare runs side by side. It's a lab notebook for machine learning that actually stays organized. MIT license, Python. Two lines of code to integrate: `wandb.init` and `wandb.log`. Works with PyTorch, TensorFlow, Keras, Hugging Face, and basically every ML framework. The visualization is where it shines: interactive charts, parameter importance plots, and run comparisons that MLflow's UI can't touch.

Free tier: unlimited personal projects, 100GB storage. That's generous for solo work. Team plan starts at $50/user/month: RBAC, audit logs, team dashboards.

Self-hosting exists (W&B Server) but it's enterprise-only. No free self-hosted option. You're on their cloud or you're paying for a private deployment. Solo ML engineers: the free tier is excellent. Use it. Small teams (2-10): $50/user/month adds up fast ($500/mo for 10 people). Compare against self-hosted MLflow at $0. Growing teams: the collaboration features justify the cost if experiment tracking is critical to your workflow.

The catch: no free self-hosted path. Once your team grows, you're locked into per-seat pricing or an enterprise contract. MLflow gives you the same core tracking for free if you're willing to run it yourself.