Training monitoring dashboard setup with TensorBoard and Weights & Biases (WandB) including real-time metrics tracking, experiment comparison, hyperparameter visualization, and integration patterns. Use when setting up training monitoring, tracking experiments, visualizing metrics, comparing model runs, or when user mentions TensorBoard, WandB, training metrics, experiment tracking, or monitoring dashboard.
View on GitHubFebruary 1, 2026
Select agents to install to:
npx add-skill https://github.com/vanman2024/ai-dev-marketplace/blob/main/plugins/ml-training/skills/monitoring-dashboard/SKILL.md -a claude-code --skill monitoring-dashboardInstallation paths:
.claude/skills/monitoring-dashboard/# Monitoring Dashboard **Purpose:** Provide complete monitoring dashboard templates and setup scripts for ML training with TensorBoard and Weights & Biases (WandB). **Activation Triggers:** - Setting up training monitoring dashboards - Tracking experiments and metrics in real-time - Comparing multiple training runs - Visualizing hyperparameters and results - Integrating monitoring into existing training pipelines - Logging custom metrics, images, and model artifacts **Key Resources:** - `scripts/setup-tensorboard.sh` - Install and configure TensorBoard - `scripts/setup-wandb.sh` - Install and configure Weights & Biases - `scripts/launch-monitoring.sh` - Launch monitoring dashboards - `templates/tensorboard-config.yaml` - TensorBoard configuration template - `templates/wandb-config.py` - WandB integration template - `templates/logging-config.json` - Unified logging configuration - `examples/tensorboard-integration.md` - Complete TensorBoard integration guide - `examples/wandb-integration.md` - Complete WandB integration guide ## Quick Start ### 1. Choose Monitoring Solution **TensorBoard (Local/Open Source):** - Free, runs locally - Best for: Single-user development, offline work - Features: Metrics, histograms, graphs, images, embeddings - Storage: Local filesystem **Weights & Biases (Cloud/Collaboration):** - Free tier available, cloud-hosted - Best for: Team collaboration, experiment comparison, production - Features: All TensorBoard features + collaboration, alerts, reports - Storage: Cloud with unlimited history **Both (Recommended for Production):** - Use TensorBoard for local development - Use WandB for team collaboration and production tracking ### 2. Setup TensorBoard ```bash # Install and configure TensorBoard ./scripts/setup-tensorboard.sh # Launch TensorBoard ./scripts/launch-monitoring.sh tensorboard --logdir ./runs ``` **Access:** Open browser to http://localhost:6006 ### 3. Setup Weights & Biases ```bash # Install and configure WandB ./sc