Lectures related to Conditional Entropy and Information Theory Concepts

Probability Distributions in Environmental Studies

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Introduction to Inference

Covers the basics of probability theory, random variables, joint probability, and inference.

Generalization Error

Explores tail bounds, information bounds, and maximal leakage in the context of generalization error.

Random Variables and Expected Value

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

Interpretation of Entropy

Explores the concept of entropy expressed in bits and its relation to probability distributions, focusing on information gain and loss in various scenarios.

Entropy Bounds: Conditional Entropy Theorems

Explores entropy bounds, conditional entropy theorems, and the chain rule for entropies, illustrating their application through examples.

Probability and Statistics

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.