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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
Tools
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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

Introducing the MLSDLC

The concept of a systems development life cycle (SDLC), or application development life cycle, has been around since the 1960s, whereby six individual processes are put in place to effectively plan, design, build, test, deploy, and maintain applications in production. While the individual phases of the process, as well as the mechanisms to implement these phases, have evolved over the years, the fundamental requirement to quickly and effectively deliver a working application into production hasn't. The following diagram shows a high-level overview of the six phases of the SDLC:

Figure 10.1 – Six phases of the SDLC

When looking closely at Figure 10.1, you should hopefully deduce a correlation with some of the processes we've encountered up until this point in the book. For example, we could assume that some of the potential activities performed during the plan and design phases of the SDLC might be similar to some of the...

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