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What's New in TensorFlow 2.0

You're reading from   What's New in TensorFlow 2.0 Use the new and improved features of TensorFlow to enhance machine learning and deep learning

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781838823856
Length 202 pages
Edition 1st Edition
Languages
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Authors (3):
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Tanish Baranwal Tanish Baranwal
Author Profile Icon Tanish Baranwal
Tanish Baranwal
Alizishaan Khatri Alizishaan Khatri
Author Profile Icon Alizishaan Khatri
Alizishaan Khatri
Ajay Baranwal Ajay Baranwal
Author Profile Icon Ajay Baranwal
Ajay Baranwal
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Toc

Table of Contents (13) Chapters Close

Preface 1. Section 1: TensorFlow 2.0 - Architecture and API Changes
2. Getting Started with TensorFlow 2.0 FREE CHAPTER 3. Keras Default Integration and Eager Execution 4. Section 2: TensorFlow 2.0 - Data and Model Training Pipelines
5. Designing and Constructing Input Data Pipelines 6. Model Training and Use of TensorBoard 7. Section 3: TensorFlow 2.0 - Model Inference and Deployment and AIY
8. Model Inference Pipelines - Multi-platform Deployments 9. AIY Projects and TensorFlow Lite 10. Section 4: TensorFlow 2.0 - Migration, Summary
11. Migrating From TensorFlow 1.x to 2.0 12. Other Books You May Enjoy

Model Inference Pipelines - Multi-platform Deployments

What do you do after a model has been trained to perfection? Use it? If the answer is yes, then how do you use it? The answer you're looking for is inference. Simply put, the process of inference is what is needed to ensure that machine learning models can be used for serving the needs of actual users. Formally put, inference is the process of computing trained machine learning models efficiently to serve the user's needs. Inference can be performed on a variety of hardware types including servers, and end user devices such as phones and web browsers. As per user requirements, it can also be performed on different operating systems.

Previous chapters have focused on the process of how to build a model. This chapter will cover a detailed overview of the inference stage. First, you will cover a detailed overview of...

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