Serving TensorFlow Models with a Custom Environment
Build a custom serving environment to run TensorFlow models with extra dependencies.
TensorFlow
TensorFlow Serving: Handling Content Types
Explore how TensorFlow Serving handles different request content types for inference.
Serving TensorFlow Models with JSON Requests
Send and parse JSON prediction requests against a TensorFlow Serving model.
Serving Custom TensorFlow Models
Package and serve a custom TensorFlow model signature with TensorFlow Serving.
Serving Multiple TensorFlow Models with Monitoring
Serve multiple TensorFlow models simultaneously and monitor them with Prometheus and Swagger.
Prepare and Deploy a TensorFlow Model to Tensorflow Serving
Serve tensorflow model efficiently with customized model signatures
Distributed Training with TensorFlow
Train TensorFlow models across multiple workers using distributed training strategies.
Autoscaling TensorFlow Serving on Kubernetes
Set up horizontal pod autoscaling for a TensorFlow Serving deployment on Kubernetes.