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Learn TensorFlow Enterprise

You're reading from Learn TensorFlow Enterprise Build, manage, and scale machine learning workloads seamlessly using Google's TensorFlow Enterprise

Product type Paperback

Published in Nov 2020

Publisher Packt

ISBN-13 9781800209145

Length 314 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Artificial Intelligence

Author (1):

KC Tung

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1 – TensorFlow Enterprise Services and Features

2. Chapter 1: Overview of TensorFlow Enterprise FREE CHAPTER

3. Chapter 2: Running TensorFlow Enterprise in Google AI Platform

4. Section 2 – Data Preprocessing and Modeling

5. Chapter 3: Data Preparation and Manipulation Techniques

6. Chapter 4: Reusable Models and Scalable Data Pipelines

7. Section 3 – Scaling and Tuning ML Works

8. Chapter 5: Training at Scale

9. Chapter 6: Hyperparameter Tuning

10. Section 4 – Model Optimization and Deployment

11. Chapter 7: Model Optimization

12. Chapter 8: Best Practices for Model Training and Performance

13. Chapter 9: Serving a TensorFlow Model

14. Other Books You May Enjoy

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Using TensorFlow Enterprise in AI Platform

In this section, we are going to see firsthand how easy it is to access data stored in one of the Google Cloud Storage options, such as a storage bucket or BigQuery. To do so, we need to configure an environment to execute some example TensorFlow API code and command-line tools in this section. The easiest way to use TensorFlow Enterprise is through the AI Platform Notebook in Google Cloud:

In the GCP portal, search for AI Platform.
Then select NEW INSTANCE, with TensorFlow Enterprise 2.3 and Without GPUs. Then click OPEN JUPYTERLAB:
Figure 1.21 – The Google Cloud AI Platform and instance creation
Click on Python 3, and it will provide a new notebook to execute the remainder of this chapter's examples:

Figure 1.22 – A JupyterLab environment hosted by AI Platform

An instance of TensorFlow Enterprise running on AI Platform is now ready for use. Next, we are going to use this platform...

You have been reading a chapter from

Learn TensorFlow Enterprise

Published in: Nov 2020

Publisher: Packt

ISBN-13: 9781800209145

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Authors (1)

Tung

Tung

KC Tung is a cloud solution architect at Microsoft and specializes in machine learning, as well as AI model development and deployment. He has a Ph.D. in biophysics from the University of Texas Southwestern Medical Center in Dallas and has spoken at the 2018 O'Reilly AI Conference in San Francisco and the 2019 O'Reilly TensorFlow World Conference in San Jose. He has worked on building data ingestion and feature engineering pipelines for custom datasets in cloud environments. He has also delivered machine learning models for scalable deployment. He is a Microsoft certified AI engineer and data engineer.

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