Lectures related to Data Compression and Shannon's Theorem: Shannon-Fano Coding

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Explores achievable rate, channel capacity, spectral efficiency, and fading channels in wireless communication systems.

Discusses challenges in determining system entropy and multiple contributions to specific heat.

Explores method dispatch optimization in object-oriented languages, focusing on inline caching and membership tests.

Explores the statistical definition of entropy, adatoms on a surface, and mixing in a solid solution.

Explores optimal transport theory with a focus on heat equations and Wasserstein distance.