Covers: theory of Joint Cumulative Distribution function

0Provides one way of expressing Joint Probability distribution which is via Joint cumulative distribution function. Understand how it is related to probability on 2 Random Variables

Read section Joint cumulative distribution function

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- Objectives
- This list will help you get an understanding about Joint Probability of >=2 Random Variables
- Potential Use Cases
- Mathematical foundations behind Deep Learning
- Who is This For ?
- INTERMEDIATE

Click on each of the following **annotated items** to see details.

ARTICLE 1. What is Joint Probability distribution

Provides intuitive understanding of Joint Probability distribution5 minutes

ARTICLE 2. Example of Joint Probability distribution

Provides an example of Joint distribution in Discrete space15 minutes

ARTICLE 3. Joint cumulative distribution function

Provides one way of expressing Joint Probability distribution which is via Joint cumulative distribution function. Understand how it is related to probability on 2 Random Variables 10 minutes

ARTICLE 4. Joint Density function / Joint Mass Function

presents another way of expressing Joint Probability distribution which is via Joint Density function (Continuous) or Joint Mass Function (Discrete)10 minutes

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