Lectures related to German tank problem

Covers Maximum Likelihood Estimation, focusing on ML Estimation-Distribution, Shrinkage Estimation, and Loss functions.

Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.

Logistic Regression: New Formulation and Loss Function

Explores a new formulation of logistic regression and its connection to empirical risk minimization.

Maximum Likelihood Estimation: Properties and Applications

Covers Maximum Likelihood Estimation properties, applications, and assumptions, providing a comprehensive understanding of MLE concepts and their practical implications.