Probability Theory: Discrete Random Variables

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.

Normal Distribution: Properties and Calculations

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Probability Theory: Basics and Applications

Covers the fundamentals of probability theory, including corollaries, conditional probability, total probability theorem, and random variables.

Linear Combinations: Moment-Generating Functions

Explores moment-generating functions, linear combinations, and normality of random variables.

Statistical Inference: Random Variables

Covers random variables, probability functions, expectations, variances, and joint distributions.

Probability Density Function: Basics

Covers the basics of Probability Density Function (PDF) in probability theory.

Probability Theory: Basics and Applications

Covers the fundamentals of probability theory, including conditional probability, Bayes' rule, and random variables.

Probability Distributions: Central Limit Theorem and Applications

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Fundamental Limits of Gradient-Based Learning

Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.

Page 2 of 2