Building Interactive Machine Learning and Data Science Applications With Streamlit

The Streamlit framework is an open-source Python library that offers an intuitive way to create web applications for machine learning and data science use cases. Streamlit is designed to be easy to use with minimal code, which clears the path for data scientists and machine learning engineers to focus on exploring and analyzing data and machine learning models.

In this lab, you will deploy a Streamlit application to an Amazon EC2 instance to begin interacting with the application. Using the deployed application as a reference, you will review the source code highlighting a few basic and interactive components of the Streamlit framework. You will learn how to render interactive elements and integrate Amazon S3 and Amazon Bedrock with the Streamlit application.

Learning objectives

Upon completion of this beginner-level lab, you will be able to:

• Deploy a Streamlit application to Amazon EC2
• Render Streamlit elements in a web application
• Integrate Amazon S3 and Amazon Bedrock with a Streamlit application

Intended audience

• Candidates for the AWS Certified Machine Learning Specialty certification
• Machine Learning Engineers
• Data Engineers
• Software Engineers

Prerequisites

Familiarity with the following will be beneficial but is not required:

• Amazon Bedrock

The following content can be used to fulfill the prerequisites:

• Invoking Amazon Bedrock Models Using the Bedrock Runtime and AWS Lambda