Week 1

Question 1

What is gradient descent?

Answer 1

An algorithm for minimizing functions so for example cost function for linear regression

Question 2

What does a:=b mean?

Answer 2

Set a to the value of b

Question 3

What does alpha represent in gradient descent algorithm?

Answer 3

The learning rate, how big a step it takes when updating parameters Øj

Question 4

In gradient descent algorithm what does derivative signify?

Answer 4

The slope of the tangent - can be positive or negative

Question 5

What is a convex function

Answer 5

Cost function for linear regression is always a bowl shaped or convex function. No local optima, only global optimum

Question 6

What is batch gradient descent?

Answer 6

Each step of gradient descent uses all the training examples (other types of gradient descent only use subset of training examples)

Question 7

What is linear regression algorithm notation?

Answer 7

hø(x) = ø0 + ø1x

Question 8

What is univariate linear regression?

Answer 8

Linear regression with one variable

Question 9

What is cost function algorithm notation?

Answer 9

J(Øo, Ø1) = 1/2m mEi=1 (hØ(xi) - yi)squared

Question 10

What is another name for cost error function?

Answer 10

Squared error function