Course Outline

TensorFlow Serving Overview

  • What is TensorFlow Serving?
  • TensorFlow Serving architecture
  • Serving API and REST client API

Preparing the Development Environment

  • Installing and configuring Docker
  • Installing ModelServer with Docker

TensorFlow Server Quick Start

  • Training and exporting a TensorFlow model
  • Monitoring storage systems
  • Loading exported model
  • Building a TensorFlow ModelServer

Advanced Configuration

  • Writing a config file
  • Reloading Model Server configuration
  • Configuring models
  • Working with monitoring configuration

Testing the Application

  • Testing and running the server

Debugging the Application

  • Handling errors

TensorFlow Serving with Kubernetes

  • Running in Docker containers
  • Deploying serving clusters

Securing the Application

  • Hiding data

Troubleshooting

Summary and Conclusion

Requirements

  • Experience with TensorFlow
  • Experience with the Linux command line

Audience

  • Developers
  • Data scientists
  7 Hours
 

Number of participants


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Dates are subject to availability and take place between 9:30 am and 4:30 pm.
Open Training Courses require 5+ participants.

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