1. Features
a. What are they? How do you come up with them? How do you extract them?
i. Example: How to make a computer tell whether a person's name is male or female
ii. Example Feature: Using the last letter of a person's name to determine gender
b. What makes a good feature?
c. Displaying features
d. Students to generate their own features and write Python code to extract
and display them
2. How do we use features to make a decision?
a. Building a Bayesian classifier
i. Intro to probability theory
a. How to define probabilistic measure on a set of events
i. Examples - dice, sets of numbers
ii. Addition of Probabilities
iii. Independence of Probabilities
iv. Conditional Probabilities
v. Bayes Theorem
a. Examples of how Bayes Theorem works
Project: Build a classifier to classify names as either male or female
Part 2 - Deliverables for Submission 12/12