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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

Chapter 3: Exploring Kubernetes

Now that you have seen that Kubernetes will form the basis of your machine learning (ML) platform, it's logical to refresh your knowledge of the underlying bedrock of our solution. Though there are many resources available on the internet on this topic of Kubernetes, we will briefly discuss the role of Kubernetes in the cloud era and the flexibility it provides for building solutions. You will also learn about Operators in Kubernetes and how they help simplify the installation and operation of Kubernetes workloads. By the end of this chapter, you will have built a running minikube instance either in your local machine or in the cloud. This is a single-node Kubernetes cluster that you will use as the base infrastructure to build and run the ML platform.

In this particular order, we will cover the following topics:

  • Exploring Kubernetes major components
  • Becoming cloud-agnostic through Kubernetes
  • Understanding Operators
  • Setting...
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