Machine Learning
A branch of AI where systems learn patterns from data and perform better without every rule being explicitly programmed.
By Tanguy De Keyzer · Founder & digital strategist
Machine learning is the branch of artificial intelligence where a system learns patterns from data instead of following fixed rules. You give the model examples, it discovers the connections itself, and it improves as it sees more quality data.
How does a model learn?
Roughly, there are three ways. With supervised learning the model gets labelled examples, for instance thousands of emails marked as spam or not-spam. With unsupervised learning it looks for structure in unlabelled data itself, useful for discovering customer segments. With reinforcement learning it learns through reward and penalty, like a bidding algorithm that learns the best ad bid.
Why it matters to marketers
Many tools you use daily run on machine learning: Smart Bidding in Google Ads, lookalike audiences, predictive lead scoring, recommendations in webshops. The language models behind AI assistants are a well-known application; see how an LLM (large language model) works. Understanding how they learn helps you give better input. A model is only as good as the data you feed it.
The pitfall
Machine learning is not magic. Poor or biased data leads to poor outcomes, and a model that optimises for the wrong goal optimises hard in the wrong direction. So always steer on a goal that truly matters, revenue and customers, and not on a number that merely looks good in a dashboard.
From theory to growth.
We turn Machine Learning into measurable results for your business.