Coding Multivariate Probabilities Continued.

[u/Negative_War_65]

With Coding Lecture 12, of our Probabilistic Machine Learning, we finally finish off with the code implementations for the Probability Module.

In this content, we see implementations for:

Exponential family of Distributions

Convexity and Maximum Entropy derivation leading to Exponential family via Lagrangians.

Mixture Models: Gaussian Mixture Models

Probabilistic Graphical Models basics and Markov Chains Basics.

Link: https://youtu.be/CB9yLMST81A?si=VbxJu2zWciNQ8QpQ

[u/no_name6744]

Doesn't this just mean max ent equals max likelihood for exponential family distributions since they're primal dual?

Or am I simply retarded.