9. Applications of ML
•Recommender systems (Amazon, Netflix, etc.)
•Face recognition / object recognition
•Machine translation
•Detecting cancer
•Search engines
11. ML vs Stats
Machine Learning
•Prediction
•Complex
•“Machine” learns
•Optimization
Stats
•Analysis / understanding
•Simple
•Humans learn
•Finding the “truth”
12. ML vs Stats (online ads)
Statisticians would ask:
•“If we show this ad, will it increase the
probability that they will buy?”
•“Is Copy A more effective than Copy B?”
13. ML vs Stats (online ads)
ML scientists would ask:
•“Which ads should we show to which
individuals to maximize profit?”