What a kernel is, what C, epsilon, gamma and the length scale mean in support vector regression and Gaussian process regression, why the inputs are scaled first, and what the uncertainty from a Gaussian process rests on. [read]
2025-11-25 / AI / series From zero / machine-learning, support-vector-regression, gaussian-processes, scikit-learn
Twelve words from the scikit-learn workflow, each explained by a run table or a calibration curve, with the name the library gives it. [read]
2025-11-25 / AI / series From zero / machine-learning, scikit-learn, vocabulary
What a decision tree, a random forest, gradient boosting and XGBoost are, what their main settings mean, and why none of them can predict beyond the range of the runs they were trained on. [read]
2025-11-25 / AI / series From zero / machine-learning, decision-trees, xgboost, scikit-learn
What the units, layers, activation and epochs of a multilayer perceptron are, why its inputs are scaled first, and why the fit on a small table changes from one start to the next. [read]
2025-11-19 / AI / series From zero / neural-networks, scikit-learn, machine-learning