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Automated Machine Learning on AWS

You're reading from   Automated Machine Learning on AWS Fast-track the development of your production-ready machine learning applications the AWS way

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801811828
Length 420 pages
Edition 1st Edition
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Author (1):
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Trenton Potgieter Trenton Potgieter
Author Profile Icon Trenton Potgieter
Trenton Potgieter
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Fundamentals of the Automated Machine Learning Process and AutoML on AWS
2. Chapter 1: Getting Started with Automated Machine Learning on AWS FREE CHAPTER 3. Chapter 2: Automating Machine Learning Model Development Using SageMaker Autopilot 4. Chapter 3: Automating Complicated Model Development with AutoGluon 5. Section 2: Automating the Machine Learning Process with Continuous Integration and Continuous Delivery (CI/CD)
6. Chapter 4: Continuous Integration and Continuous Delivery (CI/CD) for Machine Learning 7. Chapter 5: Continuous Deployment of a Production ML Model 8. Section 3: Optimizing a Source Code-Centric Approach to Automated Machine Learning
9. Chapter 6: Automating the Machine Learning Process Using AWS Step Functions 10. Chapter 7: Building the ML Workflow Using AWS Step Functions 11. Section 4: Optimizing a Data-Centric Approach to Automated Machine Learning
12. Chapter 8: Automating the Machine Learning Process Using Apache Airflow 13. Chapter 9: Building the ML Workflow Using Amazon Managed Workflows for Apache Airflow 14. Section 5: Automating the End-to-End Production Application on AWS
15. Chapter 10: An Introduction to the Machine Learning Software Development Life Cycle (MLSDLC) 16. Chapter 11: Continuous Integration, Deployment, and Training for the MLSDLC 17. Other Books You May Enjoy

Understanding the security lens

Securing the solution is a critically important task within the MLSDLC. While the majority of common MLSDLC implementations typically deal with security issues as and when they arise, it is a good practice to proactively assess the overall security posture of the final application before it's deployed into production.

So, instead of performing a full security audit on the ACME web application, this section will highlight some of the best practices that the security team should follow, by showing how they interact with other members of the cross-functional team. The following diagram shows the overall role that the security team plays within the MLSDLC process:

Figure 10.7 – The security team's role within the MLSDLC process

As Figure 10.7 shows, the first thing the security team needs to do is review how data is used, by working with the data team.

Securing the data

The following guidelines should be...

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