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