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Automated Machine Learning with Microsoft Azure

You're reading from   Automated Machine Learning with Microsoft Azure Build highly accurate and scalable end-to-end AI solutions with Azure AutoML

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800565319
Length 340 pages
Edition 1st Edition
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Authors (2):
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Dennis Michael Sawyers Dennis Michael Sawyers
Author Profile Icon Dennis Michael Sawyers
Dennis Michael Sawyers
Dennis Sawyers Dennis Sawyers
Author Profile Icon Dennis Sawyers
Dennis Sawyers
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Table of Contents (17) Chapters Close

Preface 1. Section 1: AutoML Explained – Why, What, and How
2. Chapter 1: Introducing AutoML FREE CHAPTER 3. Chapter 2: Getting Started with Azure Machine Learning Service 4. Chapter 3: Training Your First AutoML Model 5. Section 2: AutoML for Regression, Classification, and Forecasting – A Step-by-Step Guide
6. Chapter 4: Building an AutoML Regression Solution 7. Chapter 5: Building an AutoML Classification Solution 8. Chapter 6: Building an AutoML Forecasting Solution 9. Chapter 7: Using the Many Models Solution Accelerator 10. Section 3: AutoML in Production – Automating Real-Time and Batch Scoring Solutions
11. Chapter 8: Choosing Real-Time versus Batch Scoring 12. Chapter 9: Implementing a Batch Scoring Solution 13. Chapter 10: Creating End-to-End AutoML Solutions 14. Chapter 11: Implementing a Real-Time Scoring Solution 15. Chapter 12: Realizing Business Value with AutoML 16. Other Books You May Enjoy

Scoring new data for many models

Scoring new data with the MMSA is a fairly straightforward task. Once you have your models trained, simply navigate to the correct notebook, change your variables to match your training notebook, and click the run button. As there are very few settings to alter compared to the training notebook, it's even easier to use with your own code.

In this section, like the others, first you will run the out-of-the-box scoring notebook with OJ Sales. Then, you will create a new notebook to score the sample data.

Scoring OJ sales data with the MMSA

To score OJ Sales data with the multiple models you've trained, follow these steps:

  1. From the solution-accelerator-many-models folder, open the Automated_ML folder.
  2. From the Automated_ML folder, open the 03_AutoML_Forecasting_Pipeline folder.
  3. Open 03_AutoML_Forecasting_Pipeline.ipynb.
  4. Run all of the cells in section 1.0. These cells set up your AMLS workspace, compute cluster...
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