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MLOps with Red Hat OpenShift
MLOps with Red Hat OpenShift

MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations

By Ross Brigoli , Faisal Masood
£26.99 £17.99
Book Jan 2024 238 pages 1st Edition
eBook
£26.99 £17.99
Print
£33.99
Subscription
£13.99 Monthly
eBook
£26.99 £17.99
Print
£33.99
Subscription
£13.99 Monthly

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Product Details


Publication date : Jan 31, 2024
Length 238 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120230
Category :
Table of content icon View table of contents Preview book icon Preview Book

MLOps with Red Hat OpenShift

Part 1: Introduction

This part covers the basic concepts of MLOps and an introduction to Red Hat OpenShift.

This part has the following chapters:

  • Chapter 1, Introduction to MLOps and OpenShift
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Key benefits

  • 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

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

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Jan 31, 2024
Length 238 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781805120230
Category :

Table of Contents

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

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