Skip to main content
Graph
Search
fr
|
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Probability Distributions: Discrete Random Variables
Graph Chatbot
Related lectures (31)
Previous
Page 3 of 4
Next
Probability and Statistics
Explores joint random variables, conditional density, and independence in probability and statistics.
Probability and Statistics
Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.
Continuous Random Variables
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Probability and Measure: Fundamentals and Applications
Covers fundamental concepts of probability theory and measure theory, including joint probabilities, random variables, and the central limit theorem.
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.
Probability Theory: Midterm Solutions
Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.
Continuous Random Variables: Distributions and Examples
Explores continuous random variables, density functions, and distribution laws with practical examples.
Probability Theory: Random Variables and Independence
Explores discrete and continuous random variables, independence, and probability functions.
Stochastic Models for Communications
Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.
Linear Regression: Theory and Applications
Covers the theory and practical applications of linear regression.