MLOps with Red Hat OpenShift / Najlacnejšie knihy
MLOps with Red Hat OpenShift

Code: 44755320

MLOps with Red Hat OpenShift

by Faisal Masood

Build and manage MLOps pipelines with this practical guide to using Red Hat OpenShift Data Science, unleashing the power of machine learning workflowsKey FeaturesGrasp MLOps and machine learning project lifecycle through concept i ... more

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Book synopsis

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

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

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.

Table of Contents

  1. Introduction to MLOps and OpenShift
  2. Provisioning an MLOps platform in the Cloud
  3. Building Machine Learning Models
  4. Embedding ML Models into the Applications
  5. Deploying ML Models as a Service
  6. Operating ML workloads
  7. Building a face detector using the Red Hat ML Platform

Book details

Book category Books in German Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik, EDV - Sonstiges

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