Configuring MWAA and Amazon SageMaker

Описание: Welcome to the third video of our series, "Building an End-to-End ML Pipeline for Malware Detection!" Today we’re going to dive into setting up our Apache Airflow environment using Amazon’s Managed Workflows for Apache Airflow (MWAA). We'll also configure an Amazon SageMaker domain for our pipeline.

In this video, we will cover:
Launching and configuring the MWAA environment to interact seamlessly with other AWS services.
Setting up an Amazon SageMaker domain for developing, training, and deploying our machine learning models.
Configuring the SageMaker execution role to access S3 resources, which is essential for storing and retrieving data and model artifacts.

To enhance your learning experience, make sure to check out these additional resources:
GitHub Repository: https://github.com/JamesFCoffey/malwa...
Medium Blog Series:   / building-an-end-to-end-ml-pipeline-for-mal...  

Stay tuned for the next video, where we set up Amazon IAM permissions for our data preprocessing with Amazon EMR Serverless. This will ensure our pipeline has all the necessary permissions to function smoothly and securely.

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Thank you for joining me on this exciting journey. Let's get started!