  Amazon Web Services (AWS) SageMaker培訓

Introduction

Understanding machine learning with SageMaker
Machine learning algorithms
Overview of AWS SageMaker Features

AWS and cloud computing
Models development
Setting up AWS SageMaker

Creating an AWS account
IAM admin user and group
Familiarizing with SageMaker Studio

UI overview
Studio notebooks
Preparing Data Using Jupyter Notebooks

Notebooks and libraries
Creating a notebook instance
Training a Model with SageMaker

Training jobs and algorithms
Data and model parallel trainings
Post-training bias analysis
Deploying a Model in SageMaker

Model registry and model monitor
Compiling and deploying models with Neo
Evaluating model performance
Cleaning Up Resources

Deleting endpoints
Deleting notebook instances
Troubleshooting

Summary and Conclusion