Deploying the Model

Difficulty: Intermediate
Duration: 3 minutes and 9 seconds
Students: 2,650
Rating: 4.8/5

This lesson takes an introductory look at using the SageMaker platform, specifically within the context of preparing data, building and deploying machine learning models.

During this lesson, you'll gain a practical understanding of the steps required to build and deploy these models along with learning how SageMaker can simplify this process by handling a lot of the heavy lifting both on the model management side, data manipulation side, and other general quality of life tools.

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Learning Objectives

  • Obtain a foundational understanding of SageMaker
  • Prepare data for use in a machine learning project
  • Build, train, and deploy a machine learning model using SageMaker

Intended Audience

This lesson is ideal for data scientists, data engineers, or anyone who wants to get started with Amazon SageMaker.

Prerequisites

To get the most out of this lesson, you should have some experience with data engineering and machine learning concepts, as well as familiarity with the AWS platform.

Covered Topics
Calculated Systems
This content is developed in partnership with Calculated Systems
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