Writing Beautiful, Idiomatic Python
Learn how to write beautiful, idiomatic Python code that will improve readability and performance.
Gaussian Mixture Models
Gaussian Mixture Models (GMMs) are a way to model an empirical distribution of data with a mixture of Gaussians.
Conditional Multivariate Gaussian Distribution
Learn how to estimate the expected values of a subset of variables given (or conditioned on) another subset with a conditional multivariate gaussian distribution.
Partial Correlation
Partial correlation, or conditional correlation, is a way to test for correlation between two variables, X and Y, given a third, Z. This technique is often useful in causal research when trying to discover confounding relationships.
Area Under the Curve
Area Under the Curve (AUC) for the receiver operating characteristic (ROC) and precision-recall (PR) curves are two semi-proper scoring rules for judging classification performance of machine learning techniques. Understand how these curves are created and how to interpret them.
Latent Dirichlet Allocation
Latent Dirichlet Allocation (LDA) is a technique used in inferring topic models from documents. Go under the hood in understanding how LDA works.
Principal Component Analysis
Principal Component Analysis (PCA) is a technique to reduce features.