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Getting Started with Amazon SageMaker JumpStart

BEGINNER
60 minutes
5 tasks

In this lab, you will explore Amazon SageMaker JumpStart, a service that provides quick access to pre-built models and solutions. You will learn how to deploy a pre-built model and make inferences, which simplifies the use of machine learning in your applications.

Scenario

A company wants to introduce machine learning capabilities in its applications but lacks the expertise to build models from scratch. By using Amazon SageMaker JumpStart, they can quickly deploy pre-built models to begin learning and making predictions, enhancing their application's functionality.

Learning Objectives

  • Understand how to use Amazon SageMaker JumpStart to deploy pre-built models.
  • Learn to make inferences using deployed models in Amazon SageMaker.
  • Explore the integration of AI services with applications without deep ML expertise.

tasks (5)

task 1: Explore the Amazon SageMaker JumpStart Console

10 min

task 2: Deploy a Pre-Built Model Using JumpStart

15 min

task 3: Run Inference Using the Deployed Model

15 min

task 4: Explore Governance and Compliance Features in SageMaker

10 min

task 5: Integrate SageMaker Outputs with an Application

10 min

Prerequisites

  • •Basic understanding of machine learning concepts
  • •Familiarity with AWS console navigation

Skills Tested

Deploying pre-built models with Amazon SageMaker JumpStartRunning inferences in Amazon SageMakerUnderstanding governance features in Amazon SageMaker

References