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Statistical Modeling and Machine Learning (IN2332)

Course 0000002209 in SS 2017

General Data

Course Type lecture
Semester Weekly Hours 4 SWS
Organisational Unit Informatics 12 - Chair of Bioinformatics (Prof. Rost)
Lecturers Julien Gagneur
Dates Tue, 14:00–17:00, MI 03.13.010

Assignment to Modules

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks 0. Univariate and simple multivariate calculus and summary of linear algebra with intuitive explanations 1. Concepts in machine learning: supervised vs. unsupervised learning, classification vs. regression, overfitting, curse of dimensionality 2. Probability theory, Bayes theorem, conditional independence, distributions (multinomial, Poisson, Gaussian, gamma, beta,...), central limit theorem, entropy, mutual information 3. Generative models for discrete data: likelihood, prior, posterior, Dirichlet-multinomial model, naive Bayes classifiers 4. Gaussian models: max likelihood estimation, linear discriminant analysis, linear Gaussian systems 5. Bayesian statistics: max posterior estimation, model selection, uninformative and robust priors, hierarchical and empirical Bayes, Bayesian decision theory 6. Frequentist statistics: Bootstrap, Statistical testing 7. Linear regression: Ordinary Least Square, Robust linear regression, Ridge Regression, Bayesian Linear Regression 8. Logistic regression and optimization: (Bayesian) logistic regression, optimization, L2-regularization, Laplace approximation, Bayesian information criterion 9. Generalized Linear Models: the exponential family, Probit regression 10. Expectation Maximization (EM) algorithm with applications 11. Latent linear models: Principle Component Anlaysis, Bayesian PCA
Links E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

SemesterTitleLecturersDates
SS 2016 Statistical Modeling and Machine Learning (IN2332) Tue, 14:00–17:00, MI 01.11.018
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