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MLOps with Red Hat OpenShift

You're reading from  MLOps with Red Hat OpenShift

Product type Book
Published in Jan 2024
Publisher Packt
ISBN-13 9781805120230
Pages 238 pages
Edition 1st Edition
Languages
Authors (2):
Ross Brigoli Ross Brigoli
Profile icon Ross Brigoli
Faisal Masood Faisal Masood
Profile icon Faisal Masood
View More author details

Table of Contents (13) Chapters

Preface 1. Part 1: Introduction
2. Chapter 1: Introduction to MLOps and OpenShift 3. Part 2: Provisioning and Configuration
4. Chapter 2: Provisioning an MLOps Platform in the Cloud 5. Chapter 3: Building Machine Learning Models with OpenShift 6. Part 3: Operating ML Workloads
7. Chapter 4: Managing a Model Training Workflow 8. Chapter 5: Deploying ML Models as a Service 9. Chapter 6: Operating ML Workloads 10. Chapter 7: Building a Face Detector Using the Red Hat ML Platform 11. Index 12. Other Books You May Enjoy

Summary

In this chapter, you have learned how to provision the platform. You have installed the Red Hat OpenShift platform, Red Hat ODS, and Pachyderm. You have seen how the MLOps components defined in the previous chapters are translated into the software components presented in this chapter. It gives you a mental model of what a complete MLOps platform would look like.

In the next few chapters, you will dive deeper into each of these components and understand how they enable your team to move forward. Now that you have learned how to install Kubernetes operators from OperatorHub. We will also be adding more open source components to your MLOps technology stack as you go through the later chapters.

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