Enterprise interest in machine learning and artificial intelligence continues to grow, with organizations dedicating increasingly large teams and resources to ML/AI projects. As businesses scale their investments, it becomes critical to build repeatable, efficient, and sustainable processes for model development and deployment.
Containers are a foundational technology for both DevOps and MLOps. Containers provide a core piece of functionality that allow a given piece of code—whether a notebook, an experiment, or a deployed model—to run anywhere. In this book we explore the role that the container orchestration system Kubernetes plays in supporting MLOps.
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