EE 5364. INFORMATION THEORY FOR DATA SCIENCE. 3 Hours.
Entropy, conditional entropy, relative entropy, mutual information, transfer entropy, data compression, Huffman coding, Shannon coding, compressive sensing, encoding of correlated data, source coding with side information, channel capacity, differential entropy, rate distortion, information theoretical foundations for data science, Bayesian inference, probabilistic reasoning, stock market and portfolio theory.