Expectation-Maximization (EM) Algorithm
Introduction
The Expectation-Maximization (EM) algorithm is an iterative approach to find the maximum likelihood estimates (MLE) of parameters in probabilistic models when the model depends on unobserved latent variables.
Triangle Inequality for P-Norm
Theorem
Deep Learning Notes - Chapter 1
Book
Stanford Machine Learning Lecture Notes
What is Machine Learning?
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