ML-E5: What AI guys need to know about AWS (or how to fake you’re a cloud engineer)

As AI guys, we’re virtually expected to be cloud engineers these days.

Here’s some minimal AWS to get you going as a data scientist or AI engineer.

ML series menu: E1 E2 E3 E4 E5 E6 E7 E8 E9

AWS

Amazon Web Services (AWS), as the world’s most comprehensive and broadly adopted cloud platform, offers numerous services crucial for AI development, deployment, and maintenance.

This article aims to provide an overview of the top AWS services, methods for code upload, available shell interfaces, and some illustrative examples of YAML code blocks for diverse applications.

Top 10 AWS Services

1. Amazon EC2 (Elastic Compute Cloud)

Amazon EC2 offers scalable computing capacity in the AWS cloud, eliminating the need for upfront investment in hardware and the time and complexity of maintaining it. With EC2, you can configure your server’s capacity, security, and networking, and manage storage, making it a great tool for AI engineers looking to run applications and workloads on virtual servers.

2. AWS Lambda

Lambda is a serverless computing service that allows you to run your code without provisioning or managing servers. It automatically scales your application based on the workload, making it a vital service…