Weights & Biases
Track ML experiments and monitor deployed models with Weights & Biases (W&B). This platform centralizes hyperparameters, metrics, and code versions, enhancing reproducibility and collaboration. It streamlines MLOps, ensuring reliable, scalable AI deployments from research to production.
5 Steps
- 1
Get Started with W&B: Sign up for a free Weights & Biases account at `wandb.ai/signup` and install the library in your development environment.
- 2
Initialize Your ML Project: Add `import wandb` and `wandb.init()` to your training script to connect your experiment to the W&B server. Replace `your-username` with your W&B username.
- 3
Log Hyperparameters & Configuration: Capture all experiment hyperparameters and configuration settings using `wandb.config` to ensure reproducibility and easy comparison across runs.
- 4
Track Metrics During Training: Integrate `wandb.log()` into your training loop to record key performance metrics (e.g., loss, accuracy) in real-time.
- 5
Visualize and Analyze Results: Navigate to your W&B project dashboard in your browser to view real-time plots, compare different experiment runs, and gain insights into model performance.
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