Developer and Machine Learning

What Developers Should Understand About Machine Learning (Before Touching a Model) Most developers don’t struggle with machine learning because the math is hard. They struggle because the explanations are disconnected from real engineering work. After years of helping people ramp up on ML, I’ve learned that the most effective way to teach it is to anchor everything in scenarios, workflows, and constraints — the things developers deal with every day. I’m Larry Dale, founder of PowerKram ( https://powerkram.com ), where I build scenario‑based learning systems for people who want to understand how ML actually works in practice, not just in theory. This post is a distilled version of the fundamentals I teach developers who are new to ML or integrating ML into their systems. Why Developers Should Care About ML Fundamentals Even if you’re not training models full‑time, ML concepts show up everywhere: data pipelines API integrations cloud services that quietly rely on ML systems that adapt to