Reliably deploying and maintaining machine learning applications is complex. There's a dizzying array of tools and they look different from the usual DevOps tools. To apply SRE skils to ML, we need to understand the specific challenges of ML build-deploy-monitor workflows. We'll use reference examples to understand the cycle in terms of data prep, training, rollout and monitoring. We'll see...
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