Principle of maximum entropy

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

Introduces maximum entropy inference for finding optimal probability distributions with minimal extra structure.

Covers Legendre transformations in thermodynamics, focusing on internal energy, state functions, entropy, and Legendre functions.

Explores model selection criteria like AIC, BIC, and Cp in statistics for data science.

Covers the concept of entanglement in bipartite systems, focusing on entropy and Schmidt decomposition.

Delves into the rigidity of negatively curved manifolds and the interplay between curvature and symmetry.

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Explores channel capacity and convex functions in information theory, emphasizing the importance of convexity.

Explores the creation of nuclei, compression, phase transitions, and properties of quark-gluon plasma.

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.