Hyperparameter Tuning With Amazon SageMaker AMT

In this lesson, you will learn about the training stage of the machine learning lifecycle using Amazon SageMaker.

Learning Objectives

• Understand the fundamentals of machine learning model training

• Explain the key concepts and applications of foundation models in SageMaker

• Describe the SageMaker training workflow, including model setup and execution

• Outline the process for hyperparameter tuning using SageMaker's Automatic Model Tuning

• Identify the key post-training actions when working with Amazon SageMaker

Intended Audience

• This lesson is designed for data scientists, machine learning engineers, and developers who want to learn about model training techniques and how to effectively use Amazon SageMaker for training traditional and foundation models.

Prerequisites

• To get the most out of this lesson, you should have some basic working knowledge of machine learning concepts and AWS cloud services.