Learn how to use Amazon SageMaker to analyze data sets and train and deploy predictive machine learning models.
Overview
Syllabus
Introduction
- Machine learning with Amazon SageMaker
- What you should know
- What is Amazon SageMaker?
- How does Amazon SageMaker work?
- Benefits of Amazon SageMaker
- Interacting with Amazon SageMaker
- Data analysis tools
- Download and import data
- Investigate data
- Data visualization: Categories
- Data visualization: Numerical
- Data summary tools
- Challenge: Describe a dataset
- Solution: Describe a dataset
- Cleaning up the data
- Preparing the model training set
- Model training
- Checking model training results
- Challenge: Train a basic model
- Solution: Train a basic model
- Deploy trained model
- Test deployed model for single record
- Test deployed model for multiple records
- Challenge: Transfer model to server
- Solution: Transfer model to server
- Review the model for accuracy
- Next steps
Taught by
Martin Kemka
