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Weights & Biases (W&B)
A popular MLOps platform for experiment tracking, model visualisation, and team collaboration in machine learning projects.
In-Depth Explanation
Weights & Biases (W&B) is an MLOps platform that helps teams track, visualise, and collaborate on machine learning experiments. Known for its excellent user interface and collaboration features.
Core products:
- Experiments: Track and visualise ML runs
- Sweeps: Automated hyperparameter tuning
- Artifacts: Version datasets and models
- Tables: Interactive data exploration
- Reports: Share findings with stakeholders
- Model Registry: Production model management
Key features:
- Real-time experiment dashboards
- Team collaboration and sharing
- Integration with all major frameworks
- Custom visualisations
- Alerts and notifications
- LLM-specific tooling
Popular integrations:
- PyTorch, TensorFlow, Keras
- Hugging Face Transformers
- LangChain, LlamaIndex
- scikit-learn, XGBoost
Business Context
W&B streamlines ML development with excellent visualisation and collaboration, valuable for teams iterating on models.
How Clever Ops Uses This
We recommend W&B for Australian teams needing strong collaboration features and polished experiment tracking for AI development.
Example Use Case
"Tracking an LLM fine-tuning project with W&B, comparing loss curves across runs, and sharing results with stakeholders via Reports."