Explores the concept of entropy expressed in bits and its relation to probability distributions, focusing on information gain and loss in various scenarios.
Discusses mutual information, data processing inequality, and properties related to leakage in discrete systems.
Explores mutual information for quantifying statistical dependence between variables and inferring probability distributions from data.
Covers information measures like entropy, joint entropy, and mutual information in information theory and data processing.
Explores decision trees for classification, entropy, information gain, one-hot encoding, hyperparameter optimization, and random forests.
Explores achievable rate, channel capacity, spectral efficiency, and fading channels in wireless communication systems.
