Foundations of Statistics

All About Your Data

Statistical Inference

Introduction to Machine Learning

Lecture Code

Missingness, Imputation, & kNN

Missing Data

Basic Methods of Imputation

K-Nearest Neighbors

Review

Lecture Code

Simple Linear Regression

Assumptions & Diagnostics

Transformations

The Coefficient of Determination

Review

Lecture Code

Multiple Linear Regression

Multiple Linear Regression

Assumptions and Diagnostics

Research Questions of Interest

Extending Model Flexibility

Review

Multiple Linear Regression Lecture Code

Generalized Linear Models

Generalized Linear Models

Logistic Regression

Maximum Likelihood Estimation

Model Interpretation

Assessing Model Fit

Review

GLM Lecture Code

Principal Component Analysis

Taking a New Perspective

Dimension Reduction

Vectors of Highest Variance

The PCA Procedure

PCA Lecture Code

Regularization & Cross Validation

Ridge & Lasso Regression

Cross-Validation

Review

Lecture Code

Cluster Analysis

K-Means Clustering

Hierarchical Clustering

Clustering Takeaways

Review

Lecture Code – K-Means

Lecture Code – Hierarchical Clustering

Trees, Bagging, Random Forests, and Boosting

Decision Trees

Bagging

Random Forests

Boosting

Variable Importance

Review

Lecture Code

Maximal Margin Classifier

Support Vector Classifier

Support Vector Machines

Multi-Class SVMs

Review

Lecture Code

Association Rule Mining

Support, Confidence, and Lift

Lecture Code

The Nature of Time Series Analysis

Learn from the Examples

Decomposition of Time Series Data

Some Examples on Non-White Noise Stationary Time Series

ARMA and ARIMA Models

Assessing Model Fit

Neural Networks & Perceptrons

Sigmoid Neurons

Network Topology & Hidden Features

Backpropagation Learning with Gradient Descent

Additional Remarks on Neural Networks

Lecture Code

Introduction to A/B Testing

Introduction to XGBoost (Advanced Content)

Installation

Gradient Boosting

eXtreme Gradient Boosting

Tree Building Algorithm

Training Objective

Parameter Introduction

Guide on Parameter Tuning