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.
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