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Machine Learning on Kubernetes

You're reading from   Machine Learning on Kubernetes A practical handbook for building and using a complete open source machine learning platform on Kubernetes

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781803241807
Length 384 pages
Edition 1st Edition
Languages
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Authors (2):
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Ross Brigoli Ross Brigoli
Author Profile Icon Ross Brigoli
Ross Brigoli
Faisal Masood Faisal Masood
Author Profile Icon Faisal Masood
Faisal Masood
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: The Challenges of Adopting ML and Understanding MLOps (What and Why)
2. Chapter 1: Challenges in Machine Learning FREE CHAPTER 3. Chapter 2: Understanding MLOps 4. Chapter 3: Exploring Kubernetes 5. Part 2: The Building Blocks of an MLOps Platform and How to Build One on Kubernetes
6. Chapter 4: The Anatomy of a Machine Learning Platform 7. Chapter 5: Data Engineering 8. Chapter 6: Machine Learning Engineering 9. Chapter 7: Model Deployment and Automation 10. Part 3: How to Use the MLOps Platform and Build a Full End-to-End Project Using the New Platform
11. Chapter 8: Building a Complete ML Project Using the Platform 12. Chapter 9: Building Your Data Pipeline 13. Chapter 10: Building, Deploying, and Monitoring Your Model 14. Chapter 11: Machine Learning on Kubernetes 15. Other Books You May Enjoy

Configuring ODH components

In Chapter 4, The Anatomy of a Machine Learning Platform, you have installed the ODH operator. Using the ODH operator, you will now configure an instance of ODH that will automatically install the components of the ML platform. ODH executes Kustomize scripts to install the components of the ML platform. As part of the code for this book, we have provided templates to install and configure all the components required to run the platform.

You can also configure what components ODH operators install for you through a manifests file. You can pass the specific configuration to the manifests and choose the components you need. One such manifest is available in the code repository of the book at manifests/kfdef/ml-platform.yaml. This YAML file is configured for the ODH operator to do its magic and install the software we need to be part of the platform. You will need to make some modifications to this file, as you will see in the following section.

This file...

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