How can I serve TensorFlow.js models in production?
You can serve TensorFlow.js models in production by using a web server to host your model files and a client-side application to load and run the models.
What are the best practices for optimizing performance?
Best practices include minimizing model size, using quantization, and leveraging caching strategies to improve load times.
Can I use TensorFlow.js with serverless architecture?
Yes, you can deploy TensorFlow.js models in a serverless architecture using platforms like AWS Lambda or Google Cloud Functions.
What tools can help with monitoring the model's performance?
You can use tools like TensorBoard for visualization, and logging frameworks to monitor performance metrics in real-time.
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