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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

Reviewing the complete picture of the ML platform

In the preceding chapters, you have built a complete ML platform on top of Kubernetes. You have installed, configured, and explored the different components of the platform. Before you start using the platform, let's take a step back and look at the platform you have built from the tooling perspective. Figure 8.1 shows the complete logical architecture of the platform:

Figure 8.1 – Logical platform architecture

The diagram in Figure 8.1 also shows the interaction of each platform component. The entire platform runs inside Kubernetes and is managed entirely by the Open Data Hub (ODH) operator. Although MinIO is not officially part of the ODH project, we have added it as another component operated by the ODH operator on the platform you just built. In the real world, you will have an S3 storage server already in place, and you will not need to include MinIO in your Kfdef file. It is also important...

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