Amazon SageMaker developer resources

Build, Train, and Deploy a Machine Learning Model with Amazon SageMaker

Efficiency Improvement：

• Amazon SageMaker Processing – Fully Managed Data Processing and Model Evaluation

• Amazon SageMaker Experiments – Organize, Track and Compare Your Machine Learning Trainings

• Amazon SageMaker Autopilot – Automatically Create High-Quality Machine Learning Models with Full Management and Visibility

• Amazon SageMaker Debugger – Debug Your Machine Learning Models

• Simplify Machine Learning Inference on Kubernetes with Amazon SageMaker Operators

Cost Savings:

• Save on Inference Costs by Using Amazon SageMaker Multi-Model Endpoints

• Managed Spot Training: Save up to 90% on Your Amazon SageMaker Training Jobs

• Lowering Total Cost of Ownership for Machine Learning and Increasing Productivity with Amazon SageMaker

Integration of Amazon SageMaker with Other Amazon Web Services Services:

• Run SQL Queries from Your SageMaker Notebooks Using Amazon Athena

• Introducing Amazon SageMaker Operators for Kubernetes

• How Amazon Web Services is Putting Machine Learning in the Hands of Every Developer and BI Analyst

• Automating Model Retraining and Deployment Using the Amazon Step Functions Data Science SDK for Amazon SageMaker

Relevant Release Series:

• Now Available on Amazon Sagemaker: the Deep Graph Library

• Amazon Sagemaker Studio: The First Fully Integrated Development Environment for Machine Learning

• Running Distributed TensorFlow training with Amazon SageMaker