Amazon SageMaker Examples
latest

Get started

  • Introduction to applying machine learning
  • Training
  • Inference

Featured examples

  • Get started with Studio
  • Framework examples
  • Model compilation with Neo
  • Bring your own container to Studio

Autopilot

  • Get started with Autopilot
  • Feature selection
  • Model explainability

Preprocessing

  • Preprocessing by data type
  • Ground Truth

Training

  • Algorithms
  • Bring your own container
  • Data types
  • Debugger
  • Distributed Training
  • Experiments
  • Frameworks
  • Hyperparameter tuning
  • Management features
  • Reinforcement learning

Inference

  • Batch transform
  • Bring your own container
  • Data types
  • Model Compilation with Neo
  • Model deployment
  • Model monitor
    • Get started with Model Monitor
      • Amazon SageMaker Model Monitor
      • PART A: Capturing real-time inference data from Amazon SageMaker endpoints
      • PART B: Model Monitor - Baselining and continuous monitoring
    • Enable model monitor
      • Enable Amazon SageMaker Model Monitor
      • Step 1: Enable real-time inference data capture
      • Step 2: Model Monitor - Baselining
      • Step 3: Enable continous monitoring
    • Visualization
      • SageMaker Model Monitor - visualizing monitoring results

Frameworks

  • Apache MXNet
  • Deep Graph Library
  • PyTorch
  • R
  • Scikit-learn
  • TensorFlow

Workflows

  • Processing
  • Spark
  • Step Functions

Advanced examples

  • Science of ML
  • AWS Marketplace

Community examples

  • Contributions
Amazon SageMaker Examples
  • Docs »
  • Batch transform »
  • Get started with Model Monitor
  • Edit on GitHub

Get started with Model Monitor¶

  • Amazon SageMaker Model Monitor
  • PART A: Capturing real-time inference data from Amazon SageMaker endpoints
  • PART B: Model Monitor - Baselining and continuous monitoring

Enable model monitor¶

  • Enable Amazon SageMaker Model Monitor
  • Step 1: Enable real-time inference data capture
  • Step 2: Model Monitor - Baselining
  • Step 3: Enable continous monitoring

Visualization¶

  • SageMaker Model Monitor - visualizing monitoring results
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