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Automated Machine Learning

You're reading from  Automated Machine Learning

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781800567689
Pages 312 pages
Edition 1st Edition
Languages
Author (1):
Adnan Masood Adnan Masood
Profile icon Adnan Masood

Table of Contents (15) Chapters

Preface Section 1: Introduction to Automated Machine Learning
Chapter 1: A Lap around Automated Machine Learning Chapter 2: Automated Machine Learning, Algorithms, and Techniques Chapter 3: Automated Machine Learning with Open Source Tools and Libraries Section 2: AutoML with Cloud Platforms
Chapter 4: Getting Started with Azure Machine Learning Chapter 5: Automated Machine Learning with Microsoft Azure Chapter 6: Machine Learning with AWS Chapter 7: Doing Automated Machine Learning with Amazon SageMaker Autopilot Chapter 8: Machine Learning with Google Cloud Platform Chapter 9: Automated Machine Learning with GCP Section 3: Applied Automated Machine Learning
Chapter 10: AutoML in the Enterprise Other Books You May Enjoy

Understanding AutoML Tables model deployment

In order to deploy the model that we trained in the previous section, perform the following steps:

  1. We must click on the TEST & USE tab to deploy the model. There are multiple ways of testing the trained model: you can either test it as a batch prediction (file-based), as an online prediction (API), or export it in a Docker container. The option at the top of the page lets you toggle between online predictions via the REST API and batch predictions. This allows you to upload a CSV file or point to a BigQuery table and get prediction results for that entire file or table. Considering the amount of time it takes to use, AutoML Tables enables you to achieve a much higher level of model performance than you could reach manually. We will be doing online API-based prediction in this section:

    Figure 9.22 – AutoML Tables – exporting the model

  2. Click on the ONLINE PREDICTION tab. You will see the following screen. Here...
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