ML Foundations for AI Engineers

A practical guide to teaching computers anything

AI (as broadly understood today) is built on top of machine learning (ML). Although modern ML models allow developers to create powerful AI apps without understanding their inner workings, this technical debt eventually comes due, causing confusion, bottlenecks, and broken apps. In this guide, I’ll cover the essentials of ML that builders need to know to be successful AI engineers.

Image from Canva.

Over the past 6 months, I’ve taught 100+ (non-ML) engineers how to build custom AI applications with LLMs. Although they can go far (and fast) with their existing technical skills, most eventually hit a wall.

The root cause of this is a lack of knowledge about fundamental ML concepts. This guide aims to help builders avoid this technical wall by reviewing the core concepts that underlie modern AI development.

Here’s an overview of what will be covered:

• Intelligence & Models
• 3 Ways Computers Can Learn