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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

Exploring the benefits of DevOps

DevOps is not just about toolsets. Say you have a tool available that can run unit tests for you. However, if the team has no culture of writing test cases, the tool would not be useful. DevOps is about how we work together on tasks that span across different teams. So, the three primary areas to focus on in DevOps are these:

  • People: Teams from multiple disciplines to achieve a common goal
  • Processes: The way teams work together
  • Technology: The tools that facilitate collaboration across different teams

DevOps is built on top of Agile development practices with the objective of streamlining the software development process. DevOps teams are cross-functional, and they have the autonomy to build software through continuous integration/continuous delivery (CI/CD). DevOps encourages teams to collaborate over a fast feedback loop to improve the efficiency and quality of the software being developed.

The following diagram illustrates...

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