MLOps with Red Hat OpenShift
eBook - PDF

MLOps with Red Hat OpenShift

A cloud-native approach to machine learning operations

  1. 238 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

MLOps with Red Hat OpenShift

A cloud-native approach to machine learning operations

About this book

Build and manage MLOps pipelines with this practical guide to using Red Hat OpenShift Data Science, unleashing the power of machine learning workflows

Key Features

  • Grasp MLOps and machine learning project lifecycle through concept introductions
  • Get hands on with provisioning and configuring Red Hat OpenShift Data Science
  • Explore model training, deployment, and MLOps pipeline building with step-by-step instructions
  • Purchase of the print or Kindle book includes a free PDF eBook

Book Description

MLOps with OpenShift offers practical insights for implementing MLOps workflows on the dynamic OpenShift platform. As organizations worldwide seek to harness the power of machine learning operations, this book lays the foundation for your MLOps success. Starting with an exploration of key MLOps concepts, including data preparation, model training, and deployment, you'll prepare to unleash OpenShift capabilities, kicking off with a primer on containers, pods, operators, and more. With the groundwork in place, you'll be guided to MLOps workflows, uncovering the applications of popular machine learning frameworks for training and testing models on the platform. As you advance through the chapters, you'll focus on the open-source data science and machine learning platform, Red Hat OpenShift Data Science, and its partner components, such as Pachyderm and Intel OpenVino, to understand their role in building and managing data pipelines, as well as deploying and monitoring machine learning models. Armed with this comprehensive knowledge, you'll be able to implement MLOps workflows on the OpenShift platform proficiently.

What you will learn

  • Build a solid foundation in key MLOps concepts and best practices
  • Explore MLOps workflows, covering model development and training
  • Implement complete MLOps workflows on the Red Hat OpenShift platform
  • Build MLOps pipelines for automating model training and deployments
  • Discover model serving approaches using Seldon and Intel OpenVino
  • Get to grips with operating data science and machine learning workloads in OpenShift

Who this book is for

This book is for MLOps and DevOps engineers, data architects, and data scientists interested in learning the OpenShift platform. Particularly, developers who want to learn MLOps and its components will find this book useful. Whether you're a machine learning engineer or software developer, this book serves as an essential guide to building scalable and efficient machine learning workflows on the OpenShift platform.

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Information

Publisher
De Gruyter
Year
2024
eBook ISBN
9781805125853

Table of contents

  1. Cover
  2. Title Page
  3. Copyright and Credits
  4. Contributors
  5. Table of Contents
  6. Preface
  7. Part 1: Introduction
  8. Chapter 1: Introduction to MLOps and OpenShift
  9. Part 2: Provisioning and Configuration
  10. Chapter 2: Provisioning an MLOps Platform in the Cloud
  11. Chapter 3: Building Machine Learning Models with OpenShift
  12. Part 3: Operating ML Workloads
  13. Chapter 4: Managing a Model Training Workflow
  14. Chapter 5: Deploying ML Models as a Service
  15. Chapter 6: Operating ML Workloads
  16. Chapter 7: Building a Face Detector Using the Red Hat ML Platform
  17. Index
  18. Other Books You May Enjoy

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Yes, you can access MLOps with Red Hat OpenShift by Ross Brigoli,Faisal Masood in PDF and/or ePUB format, as well as other popular books in Computer Science & Data Modelling & Design. We have over one million books available in our catalogue for you to explore.