Data Engineering : Extract live Data Collection from images and logs

Learning path | 3 resources | Published on May 3, 2024
Alex Krikos Ramakrishna Yekulla

In this learning exercise, we are going to explore the complete MLOps pipeline, utilizing OpenShift AI. The MLOps pipeline includes storing models in object storage like S3, fetching models in OpenShift AI, and model serving.

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  1. Overview: Data Engineering : Extract live Data Collection from images and logs
  2. Prerequisites and step-by-step guide Page
  3. Additional resources Page

Overview: Data Engineering : Extract live Data Collection from images and logs

Data Engineering

The world of machine learning (ML) is rife with potential, but transitioning robust models from experimentation to production can be a complex journey. This is where MLOps comes in, bridging the gap between data science and application development. In this learning exercise, we'll explore how Red Hat OpenShift AI, a powerful MLOps platform, empowers you to streamline your ML workflow.