Machine Learning
From classical algorithms to modern training pipelines.
7 articles
Classical ML
Regression, trees, SVMs, and ensembles.
Synthetic Dataset Generator
Generate regression and multi-class classification datasets on the fly — linear, polynomial, moons, spirals, checkerboards — and export them as CSV.
Logistic Regression, Interactively
Build intuition for logistic regression by training one live in your browser — adjust the learning rate, watch the decision boundary move, no backend required.
Polynomial Regression: Predict Ad Revenue
Part 5 of the ML Regression Lab. Capture nonlinear, diminishing-returns trends by adding a squared feature — fit a curve to ad-spend vs. revenue using plain LinearRegression.
One-Hot Encoding: Predict Streaming Revenue
Part 4 of the ML Regression Lab. Handle a multi-category feature the right way — one-hot encode subscription tiers and predict a streaming user's monthly revenue.
Binary Encoding: Predict Auto Insurance Premiums
Part 3 of the ML Regression Lab. Models only understand numbers — learn to convert a yes/no feature into 1/0 with binary encoding, then predict insurance premiums.
Multiple Linear Regression: Predict Energy Consumption
Part 2 of the ML Regression Lab. Extend regression to several features — predict energy use from temperature and humidity — and learn to read multi-feature coefficients.
Simple Linear Regression: Predict Housing Prices
Part 1 of the ML Regression Lab. Build, evaluate, and deploy a one-feature linear regression model that predicts house prices from area — the full workflow, end to end.