Flashcards
11,105 cards in 101 decks, written from the same source as the concepts. Space to flip, arrows to move, K and R to sort what you know from what you do not. Progress lives in your browser.
Classical ML & Statistical Learning
The statistics and non-neural models that still decide most production predictions.
Statistical Inference
Estimators, likelihood, the bootstrap, hypothesis testing, multiplicity and what a confidence interval really…
Classical Supervised Learning
Linear and logistic regression, regularisation, margins, kernels, and the geometry underneath them.
Trees & Ensembles
Impurity splitting, bagging, random forests, gradient boosting, and the engineering inside XGBoost and LightGBM.
Unsupervised Learning
Clustering, mixture models and EM, PCA and SVD, manifold embeddings, and density estimation.
Bayesian Methods
Priors and posteriors, MCMC and HMC, variational inference, Gaussian processes and model comparison.
Feature Engineering
Encoding, missingness, selection, target leakage, and the train-serve skew that eats offline gains.