Week 1

Question 1

What is the (Euclidean) Distance between 2 points?

Answer 1

The distance between two points is change in y + change in x

Question 2

What is the derivative of a function?

Answer 2

The rate of change of y with respect to the change of x is called the derivative, of the function w.r.t. x

Question 3

How do you find the minimum (or max) of a function

Answer 3

Differentiate and find the point where the value is 0

Question 4

Attributes (in machine learning)

Answer 4

Pieces of information that are inputted to a machine in order to help develop a computational model

Question 5

What is the notation for machine learning?

Answer 5

*Check slides

Question 6

Annotated Data

Answer 6

existing, already labeled, data

Question 7

Training Data

Answer 7

unlabelled annotated data

Question 8

Two model types

Answer 8

1. Mathematical Function

2. Input Values as Examples (Comparison)

Question 9

Types of Input Attributes

Answer 9

Numerical, Ordinal, Categorical

Question 10

Types of Output Attributes

Answer 10

Numeric and continuous, Categorical

Question 11

Regression

Answer 11

Where the output is numeric, single input attribute

Question 12

Classification

Answer 12

Separates observations into different classes, two input attributes

Question 13

Univariate

Answer 13

One independent variable

Question 14

“New” values

Answer 14

unseen values for the model

Question 15

L1 Loss

Answer 15

Sum of absolute values of distance

Question 16

L2 Loss

Answer 16

Sum of squares of distance

Question 17

Gradient Descent

Answer 17

an algorithm used to find the minimum error in AI

Question 18

Hypothesis Function

Answer 18

function we believe the final trend looks like

Question 19

Cost Function

Answer 19

function that tells us how bad each instance of the hypothesis is

Question 20

Differential of the cost function

Answer 20

Gradient descent is used on this function

Question 21

Multivariate Regression

Answer 21

Multiple input attributes