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コース概要
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
要求
- Experience with application development
- Familiarity with Amazon Web Services (AWS) Console
Audience
- Data scientists
- Developers
21 時間
お客様の声 (3)
トレーナーはコンセプトをよく理解していました
Josheel - Verizon Connect
コース - Amazon Redshift
Machine Translated
All good, nothing to improve
Ievgen Vinchyk - GE Medical Systems Polska Sp. Z O.O.
コース - AWS Lambda for Developers
IOT applications