Introduction

Probability

Brief review of Probability Theory

Discrete Random Variable

Bayes rule

Independence and Conditional Independence

Continuous Random Variable

Mean, Variance, Quantiles

Discrete Distribution

Binomial and Bernoulli Distribution

Poisson Distribution

Continuous Distribution

Gaussian(Normal) Distribution

Student t distribution

Chi-Square Distribution

Gamma Distribution

Beta Distribution

Joint Probability Distribution

Covariance and Correlation

Information Theory

Entropy: JE

KL divergence: JE

Statistical Hypothesis Test

Statistical and P-value

Student t-test

Chi-Square Test

Multiple Testing

ANOVA

Multi-Armed Bandit

Bayesian Inference and Statistics

Bayesian Inference Concept

Discrete Prior: Done

Updating Probabilistic prediction: YJ

Continuous Prior: JH

Bayesian Classifier

Bayesian Statistics

MAP

Regression

Linear Regression

MLE

Bayesian Linear Regression

Logistic Regression

Bayesian Logic Regression

Statistical ML

Bootstrap

Boosting

Bagging and Random Forest

K-NN

Unsupervised ML

K-Means

PCA