Writing · Tag
Everything I've written that touches on Machine Learning.
- TechnologyFinding Grape Varieties Without Labels: PCA and K-Means, Step by StepGiven the chemistry of 178 wines and no labels, can a machine discover that they come from three grape varieties? It can, but only if you get one preprocessing step right.
- TechnologyNaive Bayes From Scratch: Counting Words to Catch SpamNaive Bayes is a classifier you can compute with a pencil. We work one out by hand, see why smoothing matters, then build a tuned sentiment classifier in scikit-learn.
- TechnologySupport Vector Machines: Margins, Kernels and Why Scaling Comes FirstAn SVM draws the widest possible street between two classes. We build one on tumour measurements, see what unscaled features do to it, and learn what C and gamma control.
- TechnologyWhat Drives Medical Insurance Costs? Linear Regression, Read ProperlyWe fit a linear regression to 1,338 insurance bills, interpret every coefficient, check the assumptions, compare Lasso, and then let the residuals show us the model we should have built.
- TechnologyRandom Forests in Practice: More Trees, Misleading Importances and Rare ClassesRandom forests are the dependable workhorse of tabular ML. We test four things people get wrong about them, on real tumour data, and one of the answers surprised me.
- TechnologyDecision Trees, Explained Through a Diabetes ScreenA decision tree is a flowchart the computer writes for you. We build one on real clinical data, read its rules in plain English, and watch it overfit.