Category: Machine Learning

In the last post, we explored simple linear regression, where one feature predicts one target. That single line already gave us pretty good insights into relationships between variables. But real-world problems don’t just depend on one factor. Let’s take some examples: House prices are influenced by more than just size. Salary depends on more than […]

When I first thought about machine learning, it seemed like a scary topic. Coming from product engineering, I often heard about models, black boxes, and mysterious choices around which model to use. It felt inaccessible and mathematical. Recently, I decided to go beyond that assumption. To my surprise, a lot of it builds on concepts […]