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  • Book Overview & Buying MLOps with Red Hat OpenShift
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MLOps with Red Hat OpenShift

MLOps with Red Hat OpenShift

By : Ross Brigoli, Faisal Masood
5 (2)
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MLOps with Red Hat OpenShift

MLOps with Red Hat OpenShift

5 (2)
By: Ross Brigoli, Faisal Masood

Overview of this book

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.
Table of Contents (13 chapters)
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Free Chapter
1
Part 1: Introduction
3
Part 2: Provisioning and Configuration
6
Part 3: Operating ML Workloads

Building a Face Detector Using the Red Hat ML Platform

In the previous chapter of this book, you learned how the Red Hat platform enables you to build and deploy ML models. In this chapter, you will see that model is just one part of the puzzle. You have to collect data and process it before it can be fed to the model and you can get a useful response. You will see how the Red Hat platform enables you to build and deploy all the components required for a real-world application.

The aim of this chapter is to introduce you to how other Red Hat services on the same OpenShift platform provide a complete ecosystem for your needs. In this chapter, you will learn about the following:

  • Building and deploying a TensorFlow model to detect faces
  • Capturing a video feed from your local laptop
  • Storing the results in Redis, running on the OpenShift platform
  • Generating an alert when the model detects a face in the feed
  • Cost optimization strategies for the OpenShift platform...

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