Learn how to optimize MLOps on AWS using Amazon SageMaker. Explore the challenges in deploying and managing machine learning models, the benefits of using SageMaker pipelines and endpoints, and the importance of data preprocessing and model monitoring.
Table of contents
How to Optimize MLOps On AWSWhat is MLOPS?Step 1: Getting Data Ready with EMRWhat is EMR and Why Do We Need It?Step 2: Train and Build ModelsStep 3: Making Models Organized with SageMaker Model RegistryStep 4: Registering and Testing Models — Ensuring Inference ExcellenceStep 5: Seamless Model Deployment — Making It EffortlessStep 6: SageMaker Endpoint Auto Scaling: Adapting to Workload ChangesStep 7: Keeping an Eye on Our Models: Model Monitoring SimplifiedStep 8: Streamlining OrganizationStep 9: Ensuring Comprehensive SecuritySummary2 Impressions