Optimize Machine Learning Models for Inference With SageMaker Neo

Difficulty: Beginner
Duration: 2 minutes and 30 seconds
Students: 5
Rating: 5/5

Welcome to this lesson on Amazon SageMaker Neo, a capability that optimizes machine learning models for inference on cloud and edge devices. 

Learning Objectives

  • Explain key challenges in machine learning model deployment

  • Describe Amazon SageMaker Neo and its benefits

  • Optimize a pre-trained ResNet50 model using SageMaker Neo

  • Deploy a Neo-optimized ResNet50 model as a SageMaker endpoint

  • Implement real-time inference with the optimized ResNet50 model

Intended Audience

  • This lesson is designed for machine learning engineers, data scientists, and DevOps professionals looking to optimize and deploy machine learning models efficiently using Amazon SageMaker Neo.

Prerequisites

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

  • Familiarity with Python programming, AWS SageMaker, and experience training machine learning models will be beneficial.

Covered Topics