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

Ross Brigoli

Faisal Masood

€33.99

5 (2 Ratings)

Paperback Jan 2024 238 pages 1st Edition

Ross Brigoli

Faisal Masood

€33.99

5 (2 Ratings)

Paperback Jan 2024 238 pages 1st Edition

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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.

Who is this book 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.

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

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What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

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AI Assistant (beta) to help accelerate your learning

Frequently bought together

€33.99

Azure Data Engineer Associate Certification Guide

€37.99

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Total € 109.97

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What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

H2N Mar 11, 2024

It is for MLOps engineers, DevOps engineers, IT architects, and data scientists interested in MLOps and the Red Hat OpenShift Data Science platform. It introduces MLOps concepts and the Red Hat OpenShift platform, walking readers through provisioning an MLOps platform in the cloud, building machine learning models with OpenShift, managing model training workflows, deploying ML models as a service, and operating ML workloads.

Amazon Verified review

Om S Mar 08, 2024

"MLOps with Red Hat OpenShift" serves as an essential tool for MLOps and DevOps engineers, data experts, and scientists keen on mastering machine learning operations (MLOps) using OpenShift. This book breaks down MLOps into digestible parts, from initial data setup to the final deployment of models, guiding readers through using OpenShift to create effective ML pipelines. It begins with fundamental MLOps concepts, preparing readers with a solid foundation and a clear understanding of OpenShift's basics, such as containers and pods.The journey continues as readers dive into MLOps workflows, exploring the integration of machine learning frameworks for model training and testing. The focus then shifts to the use of Red Hat OpenShift Data Science and partner components like Pachyderm and Intel OpenVino. These tools play critical roles in managing data pipelines and deploying and monitoring machine learning models.Step-by-step instructions ensure that readers can follow along with ease, making the complexities of MLOps workflows manageable and understandable. The book not only educates on building MLOps pipelines for automation but also delves into model serving techniques using advanced tools like Seldon and Intel OpenVino.Targeted at MLOps and DevOps engineers, data architects, and scientists interested in leveraging OpenShift for machine learning, this book is also an invaluable resource for developers eager to learn about MLOps components. It effectively demystifies the process of building scalable and efficient machine learning workflows on the OpenShift platform, offering readers the skills needed for MLOps success.

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

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