Text and Images: Multimodal Learning on SageMaker

Welcome to the Text and Images: Multimodal Learning on SageMaker workshop. In this workshop we are going to cover:

Download and explore the dataset that contains text, images and tabular data.
Train a miltimodal autoMM model using a Amazon SageMaker training job
Perform batch inference using a Amazon SageMaker Processing job

We will use AutoGluon for Multimodal model training and inference. AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data. This example shows how to use AutoGluon MultiModal with Amazon SageMaker by using prebuilt AutoGluon containers.

Getting Started

For this workshop you’ll get access to a temporary AWS Account already pre-configured with Amazon SageMaker Notebook Intances. Follow the steps in this section to login to your AWS Account and download the workshop material.

1. To get started navigate to - https://dashboard.eventengine.run/login

Click on Accept Terms & Login

2. Click on Email One-Time OTP (Allow for up to 2 mins to receive the passcode)

3. Provide your email address

4. Enter your OTP code

5. Click on AWS Console

6. Click on Open AWS Console, remember to only use 'us-west-2' unless otherwise directed by event operator

7. In the AWS Console search for SageMaker and click on the Amazon SageMaker in the Services

8. Click on Amazon SageMaker Notebook -> Notebook Instances and then click on Open JupyterLab

9. You should now have Amazon SageMaker Notebook Jupyterlab interface open on your browser

10. Open a new terminal window

11. Clone the workshop content

In the terminal paste the following commands to clone the workshop content repo:

 cd SageMaker
 git clone https://github.com/aws-samples/sagemaker-multimodal-workshop.git

aws-samples/sagemaker-multimodal-workshop