Introduction to Kubernetes for MLOps Engineers
Kubernetes core concepts and architecture (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 22)
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Week 3 Review: The Cloud ML Workflow, End-to-End
Consolidate everything from cloud storage through SageMaker training to a live inference endpoint, then put a price tag on running it in production. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 21)
SageMaker Model Deployment & Endpoints
Take your trained machine learning models from the registry to production by deploying scalable, secure, and highly available real-time inference endpoints with Amazon SageMaker. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 20)
Introduction to AWS SageMaker Training Jobs
Running ML training in the cloud with SageMaker. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 19)
Cloud Storage for ML: S3 and GCS Basics
Your models and datasets need a home that isn't your laptop. Today we set up S3 buckets, lock down access with IAM, move files with boto3, and connect DVC straight to the cloud. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 18)
Introduction to Cloud Platforms for MLOps
Overview of AWS, GCP, and Azure ML services. (MLOPS: ABSOLUTE BEGINNERS TO PRO IN 100 DAYS - DAY 17)