Lecture 7

Question 1

Supervised Learning

Answer 1

Supervised learning is a type of machine learning where a model is trained on a labeled dataset, consisting of input-output pairs.

Question 2

Supervised learning examples

Answer 2

1. spam detector email, model is trained to detect email considered as spam
2. medical diagnosis, model is trained to distinguish healthy and diseased
3. credit scoring, to know individuals credit score

Question 3

Unsupervised learning

Answer 3

Unsupervised learning is a category of machine learning where the algorithm is trained on unlabeled data.

Question 4

Unsupervised learning

Answer 4

1. customer segmentation in marketing
2. image and document clustering
3. anomaly detection in network security

Question 5

multiple vs logistic regression

Answer 5

multiple regression: Used when the dependent variable is continuous and has a wide range of possible values. The output is a numeric value.

logistic regression: Used when the dependent variable is binary or categorical (usually representing two classes). The output is a probability score that is transformed using the logistic function.