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Flashcards in Week 1 Deck (21)
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1
Q

What is the (Euclidean) Distance between 2 points?

A

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

2
Q

What is the derivative of a function?

A

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

3
Q

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

A

Differentiate and find the point where the value is 0

4
Q

Attributes (in machine learning)

A

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

5
Q

What is the notation for machine learning?

A

*Check slides

6
Q

Annotated Data

A

existing, already labeled, data

7
Q

Training Data

A

unlabelled annotated data

8
Q

Two model types

A
  1. Mathematical Function

2. Input Values as Examples (Comparison)

9
Q

Types of Input Attributes

A

Numerical, Ordinal, Categorical

10
Q

Types of Output Attributes

A

Numeric and continuous, Categorical

11
Q

Regression

A

Where the output is numeric, single input attribute

12
Q

Classification

A

Separates observations into different classes, two input attributes

13
Q

Univariate

A

One independent variable

14
Q

“New” values

A

unseen values for the model

15
Q

L1 Loss

A

Sum of absolute values of distance

16
Q

L2 Loss

A

Sum of squares of distance

17
Q

Gradient Descent

A

an algorithm used to find the minimum error in AI

18
Q

Hypothesis Function

A

function we believe the final trend looks like

19
Q

Cost Function

A

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

20
Q

Differential of the cost function

A

Gradient descent is used on this function

21
Q

Multivariate Regression

A

Multiple input attributes