Automating AWS with Boto3 Part 2: Deploying PyTorch Models
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Automating AWS with Boto3 Part 2:
Deploying PyTorch Models

  • Learn how to deploy PyTorch models on AWS using Boto3, automate inference pipelines,
    and scale machine learning workflows in the cloud.
  • Master AWS Lambda, SageMaker, and Boto3 to seamlessly deploy and serve PyTorch
    models for efficient, serverless predictions.
  • Discover best practices for automating model deployment, managing endpoints, and
    optimizing performance when running PyTorch on AWS.

Created by Selva Prabhakaran

  • Actively updating

  • English

  • English captions

What you will learn

01

How to Deploy a PyTorch image recognition model in the serverless AWS Lambda service.

02

Enable event triggering via S3 storage and do batch inferencing of uploaded images

03

Store the results in S3

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

  • 4.5+Instructor rating

  • 200+ reviews

  • 75K+students

  • 50+ Courses

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