Book Image

Learn TensorFlow Enterprise

By : KC Tung
Book Image

Learn TensorFlow Enterprise

By: KC Tung

Overview of this book

TensorFlow as a machine learning (ML) library has matured into a production-ready ecosystem. This beginner’s book uses practical examples to enable you to build and deploy TensorFlow models using optimal settings that ensure long-term support without having to worry about library deprecation or being left behind when it comes to bug fixes or workarounds. The book begins by showing you how to refine your TensorFlow project and set it up for enterprise-level deployment. You’ll then learn how to choose a future-proof version of TensorFlow. As you advance, you’ll find out how to build and deploy models in a robust and stable environment by following recommended practices made available in TensorFlow Enterprise. This book also teaches you how to manage your services better and enhance the performance and reliability of your artificial intelligence (AI) applications. You’ll discover how to use various enterprise-ready services to accelerate your ML and AI workflows on Google Cloud Platform (GCP). Finally, you’ll scale your ML models and handle heavy workloads across CPUs, GPUs, and Cloud TPUs. By the end of this TensorFlow book, you’ll have learned the patterns needed for TensorFlow Enterprise model development, data pipelines, training, and deployment.
Table of Contents (15 chapters)
1
Section 1 – TensorFlow Enterprise Services and Features
4
Section 2 – Data Preprocessing and Modeling
7
Section 3 – Scaling and Tuning ML Works
10
Section 4 – Model Optimization and Deployment

Creating a data warehouse

We will use a simple example of putting data stored in a Google Cloud bucket into a table that can be queried by BigQuery. The easiest way to do so is to use the BigQuery UI. Make sure it is in the right project. We will use this example to create a dataset that contains one table.

You can navigate to BigQuery by searching for it in the search bar of the GCP portal, as in the following screenshot:

Figure 1.13 – Searching for BigQuery

You will see BigQuery being suggested. Click on it and it will take you to the BigQuery portal:

Figure 1.14 – BigQuery and the data warehouse query portal

Here are the steps to create a persistent table in the BigQuery data warehouse:

  1. Select Create dataset:

    Figure 1.15 – Creating a dataset for the project

  2. Make sure you are in the dataset that you just created. Now click CREATE TABLE:

    Figure 1.16 – Creating a table for the dataset

    In the...