Chapter 12. Testing, optimizing, and deploying models

—WITH CONTRIBUTIONS FROM YANNICK ASSOGBA, PING YU, AND NICK KREEGER

This chapter covers

  • The importance of and practical guidelines for testing and monitoring machine-learning code
  • How to optimize models trained in TensorFlow.js or converted to TensorFlow.js for faster loading and inference
  • How to deploy TensorFlow.js models to various platforms and environments, ranging from browser extensions to mobile apps, and from desktop apps to single-board computers

As we mentioned in chapter 1, machine learning differs from traditional software engineering in that it automates the discovery of rules and heuristics. The previous chapters of the book should have given you a solid understanding ...

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