Μαθήματα

Probability spaces, Random Variables and Stochastic Processes, Conditional Probability, Expected Values, Conditional Expectations, Independence of Random Variables. The Bernoulli Stochastic Process and Sums of Independent Random Variables: Bernoulli Process, Number of Successes, Times of Successes, Sums of Independent Random Variables, Chebyshev Inequality, Weak and Strong Law of Large Numbers, Central Limit Theorem.
Basics of Inference and Testing (including maximum likelihood estimates, hypothesis testing, likelihood ratio test, and Bayesian inference), Linear regression models, Generalized linear regression models (including logistic regression), Nonparametric Regression (including Gaussian Process regression), Tree methods and Forests, Bagging and Ensemble methods, Statistical Computing.

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