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
Exponential Family: Maximum Entropy Distributions
Graph Chatbot
Related lectures (29)
Previous
Page 1 of 3
Next
Advanced Probabilities: Random Variables & Expected Values
Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.
Probability Distributions in Environmental Studies
Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.
Elements of Statistics: Probability and Random Variables
Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.
Continuous Random Variables
Covers continuous random variables, probability density functions, and distributions, with practical examples.
Probability and Statistics
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Probability Models: Fundamentals
Introduces the basics of probability models, covering random variables, distributions, and statistical estimation.
Convergence of Random Variables
Explores the convergence of random variables, the law of large numbers, and the distribution of failure time.
Special Families of Models
Explores completeness, minimal sufficiency, and special statistical models, focusing on exponential and transformation families.
Continuous Random Variables
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
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.