How can I monitor TensorFlow.js models in production?
An example of an AI chatbot conversation about monitoring TensorFlow.js models in production.
How can I monitor TensorFlow.js models in production?
You can monitor TensorFlow.js models by tracking performance metrics, logging predictions, and using visualization tools.
What specific metrics should I track?
Key metrics include accuracy, latency, throughput, and resource usage. Monitoring these helps ensure optimal performance.
Are there any tools you recommend for visualization?
Yes, tools like TensorBoard, Grafana, and custom dashboards can help visualize model performance effectively.
How can I log predictions from my model?
You can log predictions by integrating logging libraries in your application to capture and store prediction data.
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