Discrete Random Variables

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (30)

Page 3 of 3

Random Variables: Expectation and Independence

Explores random variables, expectation, and independence in probability theory.

Calculations of Expectation

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

Statistical Inference: Random Variables

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

Probability Theory: Random Variables and Independence

Explores discrete and continuous random variables, independence, and probability functions.

Random Variables and Expected Value

Introduces random variables, probability distributions, and expected values through practical examples.

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.

Conditional Density and Expectation

Covers conditional density, independence of random variables, expectation, and variance calculation.

Convergence of Random Variables

Explores different modes of convergence for random variables.

Probability and Statistics

Covers probability, statistics, independence, covariance, correlation, and random variables.

Linear Combinations: Moment-Generating Functions

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