# Basics

Discriminative model: The conditional probability of class label on data (posterior) $p(C_k\mid x)$ …

Contrastive models learn to compare1. Contrastive use special objective functions such as NCE Noise …

The task of GAN is to generate features $X$ from some noise $\xi$ and class labels $Y$, \xi, Y \to …

Gibbs sampling is a sampling method for Bayesian inference and MCMC

ROC is used to judging the performance of classifiers

Confusion Matrix It is much easier to understand the confusion matrix if we use a binary …

hypothesis testing is about the probability of alternative hypothesis if the null hypothesis is true, or even more general

In statistics, we work with samples. For example, the sample mean is easily calculated. However, it …

Frequent patterns using association rules

Essential knowledge of computations

A brief overview of machine learning

Unsupervised Learning! Principle components analysis Clustering K-means Clustering Algorithm: …

C++ as a programming language

Python as a programming language