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Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.
Explores model selection in statistics, discussing principles, probabilistic models, characteristics evaluation, and data visualization methods.
Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.
Covers the concept of eigenfunctions of H as bases for irreducible representations and integrals.
Explores the application of linear algebra in data science, covering variance reduction, model distribution theory, and maximum likelihood estimates.
