Binary Classifier

Outlines creation of a predictive model used to determine whether credit card applicants should be approved or rejected for a credit card based on various creditworthiness metrics.

  1. Engineering a Metric
  2. Quantifying Binary Classifier Value
  3. Information Gain
  4. Selecting an Optimum

Hypothesis Testing

Cleans, compiles, and tests a dataset to evaluate the hypothesis that the financial value of homes in University towns are less effected by recessions.

Demonstrates matplotlib visuals and execution of a statistical t-test using a simple dataset that demonstrates the Stroop Effect.