Lectures related to Harmonic mean

Geometric Means: Ancient Theories and Modern Applications

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

Boundary Conditions in Harmonic Functions

Explains harmonic functions and their boundary conditions, including Dirichlet and Robin conditions.

Explores the classification and practical applications of symmetries in 3D space, emphasizing user-driven determination of object symmetries.

Harmonic Mean: Geometric Projective Geometry

Explores the harmonic mean in visual arts and projective geometry, discussing historical context and invariance properties.

Geometric Transformations: Meanings and Applications

Explores geometric transformations, invariant properties, and mean relationships in modern geometry.

Replica Symmetry Breaking: Random Energy Model

Explores Replica Symmetry Breaking in the Random Energy Model, focusing on configurations, variance, mean, and system behavior.

Random Numbers Visualization

Explains how constants affect the mean and variance of random numbers.

Statistical Inference: Weighted Mean and Radioactive Decay

Introduces weighted mean calculation and radioactive decay concept with probability estimation.

Measures of central tendency

Covers mean, median, mode, box plots, and histograms in datasets.

Probability Distributions: Moments and Transformations

Covers moments computation and probability distribution transformations.

Kernel Regression: Weighted Average and Feature Maps

Covers kernel regression and feature maps for data separability.

Stochastic Models for Communications: Continuous-Time Stochastic Processes - Stationarity

Covers the concept of stationarity in continuous-time stochastic processes and its implications in communication systems.

Statistics: Exploratory Data Analysis

Introduces statistics basics, including data analysis and probability theory, emphasizing central tendency, dispersion, and distribution shapes.

Numpy: Broadcasting, Operations, Comparisons, and Constants

Covers broadcasting, operations, comparisons, and numpy constants like pi, e, and infinity.

Martingales and Brownian Movement

Explores martingales, Brownian movement, mean numbers, and generation hypotheses.

ECDF and Quantiles

Covers ECDF, quantiles, mean, median, and box plots for dataset analysis.

Maximum Principle in Harmonic Functions

Explores the maximum principle in harmonic functions and its implications for uniqueness and bounds on solutions.

Introduction to PDES

Covers harmonic functions, Laplacian operator, Dirichlet and Robin problems, and sub-harmonic functions in Partial Differential Equations.

All of Probability: Basic Bounds, LLN & CLT

Introduces basic bounds, LLN, and CLT in probability theory, emphasizing convergence to normal distribution.

Probabilities and Statistics: Key Theorems and Applications

Discusses key statistical concepts, including sampling dangers, inequalities, and the Central Limit Theorem, with practical examples and applications.