Deep Learning - Crash Course 2023 - Random Variable - Types

The video tutorial explains the concept of random variable functions, focusing on mapping objects to discrete values. It contrasts discrete values, like color and shape, with continuous values, such as height and weight. The course will concentrate on discrete random variables, using examples like images of animals to demonstrate probability mapping to different classes.

What is the primary purpose of a random variable function as introduced in the first section?

• To map objects to continuous values

• To map objects to discrete values

• To generate random numbers

• To classify objects without probabilities

Which of the following is an example of a discrete random variable?

• Weight

• Height

• Temperature

• Nationality

What type of values do continuous random variables map to?

• Imaginary values

• Categorical values

• Discrete values

• Real values

In the context of this course, what will the focus be on?

• Continuous random variables

• Discrete random variables

• Both continuous and discrete random variables

• Neither continuous nor discrete random variables

How are objects classified in the context of discrete random variables?

• By generating random numbers

• By mapping to continuous values

• By mapping to classes with probabilities

• By using a deterministic function