Machine Learning and Computation Statistics


This is a teaching partnership between the Africa Center of Excellence in Data Science at the University of Rwanda and the Institute of Applied Computational Science at Harvard University.

View the Project on GitHub onefishy/Rwanda-Data-Science

Week 3: Bayesian Models

Day 1: Data Pre and Post-processing

Topic 1: Encoding and Transforming Data

Topic 2: Pre-Processing Data

Topic 3: Sources of Bias in Model Interpretation and Usage

In-Class Exercise: Data Preprocessing and Model Interpretation Notebook

Day 2: Dimensionality Reduction

Topic 1: Variable Selection

Topic 2: Principal Component Analysis

In-class Exercise: PCA and Dimensionality Reduction

Day 3: Introduction to Bayesian Models

Topic 1: Bayesian Models for Regression

Topic 2: Bayesian Linear and Polynomial Regression

Topic 3: Interpreting the Posterior Predictive

In-class Exercise: Bayesian Linear and Polynomial Regression

Day 4: More on Bayesian Models

Topic 1: Connecting Bayesian and Non-Bayesian Models

Topic 2: Bayesian Logistic Regression

In-Class Exercise: Bayesian Versus Frequentist Uncertainties