Part 2 of deploying your ML models to the cloud with SageMaker (MLOps) 
MLOps is deploying your ML models to the cloud. See <a href="https://madewithml.com/">MadeWithML</a> for an overview of tooling (also generally a great ML educational run-down.)
<ul>
<li><a href="https://aws.amazon.com/sagemaker/">SageMaker</a></li>
<li><a href="https://aws.amazon.com/sagemaker/getting-started/">Jumpstart</a></li>
<li><a href="https://aws.amazon.com/sagemaker/deploy/">Deploy</a></li>
<li><a href="https://aws.amazon.com/sagemaker/pipelines/">Pipelines</a></li>
<li><a href="https://aws.amazon.com/sagemaker/model-monitor/">Monitor</a></li>
<li><a href="https://aws.amazon.com/sagemaker/kubernetes/">Kubernetes</a></li>
<li><a href="https://aws.amazon.com/sagemaker/neo/">Neo</a></li>
</ul>

Tyler Renelle

MLA 016 SageMaker 2

Part 2 of deploying your ML models to the cloud with SageMaker (MLOps) MLOps is deploying your ML models to the cloud. See MadeWithML for an overview of tooling (also generally a great ML educational run-down.) SageMaker Jumpstart Deploy Pipelines Monitor Kubernetes Neo

Machine Learning Guide Episode #48

MLA 016 SageMaker 2