Covers: theory of Joint Probability density function/ probability mass function

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

Read section Joint density function or mass function

Wikipedia

Hardik Sahi**Total time needed: **~20 minutes

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

Go through the following **annotated items** *in order*:

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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