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Related lectures (32)

Page 2 of 4

Probabilistic Linear Regression

Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.

Probability and Statistics: Basics and Applications

Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.

Internal Energy and Specific Heat

Covers the calculation of internal energy and specific heat for gases, electrons, phonons, and photons.

Eliminating Nuisance Parameters: Lemmas in Statistical Inference

Explores the elimination of nuisance parameters in statistical models using Lemmas 14 and 15.

Statistical Inference: Model Selection and Nuisance Parameters

Covers model selection, nuisance parameters, and higher-order inference methods in statistical inference.

Fracture Mechanics: Crack Growth and Weakest Link

Explores fracture mechanics, crack growth, and the weakest link theory, emphasizing the statistical distribution of crack sizes and the significance of the largest crack in material failure.

Statistical Inference: Weighted Mean and Radioactive Decay

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

Gaussian Processes: Designing Receivers

Covers the theory behind Gaussian processes and the design of receivers using MAP calculations.

Applications of Machine Learning

Explores applications of machine learning, biased datasets, statistical distributions, and software demos.

Statistical Inference: Confidence Intervals

Covers the construction of approximate confidence intervals using the central limit theorem for large sample sizes.