MLOps with Open Shift offers practical insights for implementing MLOps workflows on the dynamic Open Shift 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 Open Shift 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 Open Shift Data Science, and its partner components, such as Pachyderm and Intel Open Vino, 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 Open Shift platform proficiently.
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