self driving car, supervising case
acerous, non-acerous
horse is categorized non-acerous
machine learning: give you bunch of example, features
pick up right feature, and you can classify new example
supervised classification examples
-from an album of tagged photos, recognize someone in a picture(facebook always dose)
-given someone’s music choices and a bunch of features of that music (tempo, genre, etc.) recommend a new song
unsupervised learning
-analyze bank data for weird-looking transactions, and flag those for fraud
-cluster students into types based on learning styles
Feature and Labels
LET IT Go
Features: intensity, tempo, genre, gender
tempo: relaxed – fast
intensity: light – soaring
She likes those, she doesn’t like
Scatter Plot
