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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

Product type Paperback

Published in Jun 2022

Publisher Packt

ISBN-13 9781803241807

Length 384 pages

Edition 1st Edition

Languages

Python

Tools

Kubernetes

Concepts

Machine Learning

Authors (2):

Ross Brigoli

Faisal Masood

View More author details

Table of Contents (16) Chapters

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

Part 1: The Challenges of Adopting ML and Understanding MLOps (What and Why)

In this section, we will define what MLOps is and why it is critical to the success of your AI journey. You will go through the challenges organizations may encounter in their AI journey and how MLOps can assist in overcoming those challenges.

The last chapter of this section will provide a refresher on Kubernetes and the role it plays in bringing MLOps to the OSS community. This is by no means a guide to Kubernetes, and you should consult other sources for a guide on Kubernetes.

This section comprises the following chapters:

Chapter 1, Challenges in Machine Learning
Chapter 2, Understanding MLOps
Chapter 3, Exploring Kubernetes

The rest of the chapter is locked

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Authors (2)

Faisal Masood

Faisal Masood

Faisal Masood is a cloud transformation architect at AWS. Faisal's focus is to assist customers in refining and executing strategic business goals. Faisal main interests are evolutionary architectures, software development, ML lifecycle, CD and IaC. Faisal has over two decades of experience in software architecture and development.

See other products by Faisal Masood

Brigoli

Brigoli

Ross Brigoli is a consulting architect at Red Hat, where he focuses on designing and delivering solutions around microservices architecture, DevOps, and MLOps with Red Hat OpenShift for various industries. He has two decades of experience in software development and architecture.

See other products by Brigoli

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