C24IO / SageMaker-Migrations-Workshop

SageMaker-MLOPs-Workshop-Agenda

SageMaker Migrations Workshop

Agenda for SageMaker Migrations Workshop

• Training

  • Experiments management
  • SageMaker script mode
  • Model Hyperparameter Tuning
  • RESNET Notebook
    • Debugging
    • Spot Training MXNet TensorFlow
  • Tensorflow Estimator Notebook
    • Distributed Training MXNet Pytorch
    • Bring your own container

• Hosting

  • Deploy model as an endpoint
    • SageMaker trained model
    • Bring your own model
    • Perform predictions
    • Auto-Scaling MXNet
    • A/B testing MXNet
    • Multi-model endpoints
  • Deploy tensorflow model as TF Serving
  • MLOPs best practices overview
    • Deployment across regions using SageMaker

• SageMaker with Kubernetes

  • SageMaker + Kubernetes Overview
  • SageMaker Operators for Kubernetes
  • KubeFlow pipelines with SageMaker Notebooks

• Data Labeling

  • GroundTruth Lab - Images
  • GroundTruth Lab - Videos

• Model Formats

  • ONNX MXNet

Sources:

• https://github.com/markproy/sagemaker-workshop
• https://github.com/aws-samples/mlops-amazon-sagemaker-devops-with-ml
• By Shreyas Subramanian - https://master.d11arstd4fhlv6.amplifyapp.com/ & https://www.shreyasdemos.ml/
• https://github.com/data-science-on-aws/workshop
• https://github.com/kubeflow/pipelines/tree/master/components/aws/sagemaker
• https://aws.amazon.com/blogs/machine-learning/introducing-amazon-sagemaker-components-for-kubeflow-pipelines/
• https://aws.amazon.com/blogs/opensource/deploy-machine-learning-models-to-amazon-sagemaker-using-the-ezsmdeploy-python-package-and-a-few-lines-of-code/