Lectures related to AM-GM Inequality

Explores the construction and mathematical properties of simple, double, and harmonic geometric means using ruler and compass.

Explores the fundamentals of attenuation correction in biomedical imaging and simplifies the process using the geometric mean at 180°.

Explains how to calculate average growth rates using arithmetic mean, geometric mean, and linear trend analysis.

Investigates how birth month influences athlete success, analyzing Japanese athletes' dataset to explore trends in birthdates and occupations.

Explains variational inference, Jensen's inequality, E-step, M-step, and MCMC sampling.

Covers eigenvectors, principal components, likelihood variables, EM algorithm, Jensen's inequality, and maximizing lower bounds.

Explores the calculation of weighted averages and interest rates, emphasizing the importance of averages in financial analysis.

Delves into ancient geometric means and their modern applications in geometry.

Explores latent variable models, EM algorithm, and Jensen's inequality in statistical modeling.

Covers types of mortgages, statistical methods, descriptive statistics, and property valuation techniques.

Delves into ancient geometric means, transformations, and projective geometry's birapports.

Explores expectation value, convex functions, weights, and inequalities in mathematical analysis.

Covers the properties of conditional expectation and Jensen's inequality in probability theory.

Introduces K-means clustering, the Gaussian mixture model, Jensen's inequality, and the EM algorithm.

Explores the historical and mathematical significance of Euclidean Division and the Divine Proportion in geometry and art.

Covers basic properties of conditional expectation and Jensen's inequality in probability theory.

Explores subgradients in convex functions, emphasizing non-differentiable yet convex scenarios and properties of subdifferentials.

Explores Euler's geometric proof for the Basel problem, showing how the series converges through circles and tangents.

Explores o-finite and finite measure spaces, probability measures, and inequalities, concluding with LP space completeness.