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

• DNB Media - Amazon Web Services Case Study:  Mobiuspace (SageMaker)
• DNB Media - Amazon Web Services Case Study: Huya Livestreaming (SageMaker)
• Gaming (DNB) - Amazon Web Services Case Study: Joyient (SageMaker)
• SmartMFG - Amazon Web Services Case Study: Hualai Technology (SageMaker)

Other AI-related Resources: https://amazonaws-china.com/cn/ai/aiml-resources/