Create Post: Optimize Machine Learning Models for Inference With SageMaker Neo

Author: DigitalDenCloud

_posts/2024/2024-11-12-optimize-machine-learning-models-for-inference-with-sagemaker-neo.md

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+---
+title: "Optimize Machine Learning Models for Inference With SageMaker Neo"
+date: 2024-11-12 08:00:00 - 0500
+categories: [AWS, Machine Learning]
+tags: [QA Learning Platform, AWS, Amazon SageMaker, Machine Learning, ResNet50, SageMaker Neo]
+image: 
+  path: /assets/img/headers/amazon-sagemaker-neo.webp
+  lqip: data:image/webp;base64,UklGRoQAAABXRUJQVlA4IHgAAAAQBACdASoUAAwAPzmGulOvKKWisAgB4CcJbACdMoADYW137XazNmf2AAD+5fCpze9mFav3Vfy1WVN489gFeTRFSnNK+Lskz0j5uO1NJevft25ImiB5X72nbQI39cYpvMKkhBxx+Hi0O92GbjVPNPMArPbT9ZcAAAA=
+---
+
+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.
+
+## Get Started
+[Optimize Machine Learning Models for Inference With SageMaker Neo](https://platform.qa.com/course/optimize-machine-learning-models-for-inference-with-sagemaker-neo-1/introduction-1730928863253-1/){:target="_blank"}