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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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Accessing the data sources

TensorFlow Enterprise can easily access data sources in Google Cloud Storage as well as BigQuery. Either of these data sources can easily host gigabytes to terabytes of data. Reading training data into the JupyterLab runtime at this magnitude of size is definitely out of question, however. Therefore, streaming data as batches through training is the way to handle data ingestion. The tf.data API is the way to build a data ingestion pipeline that aggregates data from files in a distributed system. After this step, the data object can go through transformation steps and evolve into a new data object for training.

In this section, we are going to learn basic coding patterns for the following tasks:

Reading data from a Cloud Storage bucket
Reading data from a BigQuery table
Writing data into a Cloud Storage bucket
Writing data into BigQuery table

After this, you will have a good grasp of reading and writing data to a Google Cloud...

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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