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17165-01 - Lecture: Machine Learning (8 CP)
| Semester | spring semester 2019 |
| Further events belonging to these CP |
17165-01 (Lecture) 17165-02 (Practical course) |
| Course frequency | Every spring sem. |
| Lecturers | Volker Roth (volker.roth@unibas.ch, Assessor) |
| Content | Introduction: What is Machine Learning? Math refresher. Supervised Learning: theoretical foundations. Regression estimation: standard methods + algorithms. Classification: standard methods + algorithms. Neural Networks and Deep Learning. Learning Theory: risk minimization, regularization, elements of statistical learning theory. Kernel Methods. Mixture models. Conditional mixtures (mixtures of experts). Clustering. Bayesian model comparison. |
| Learning objectives | Understand the theoretical foundations of Machine Learning Understand and apply practical learning algorithms: linear and generalized linear models for regression and classification, neural networks, Support Vector machines & kernel methods, mixture models & clustering. Program in Matlab, Python and Tensorflow |
| Bibliography | tba |
| Comments | Target group: Master students |
| Weblink | Course website |
| Admission requirements | Knowledge and skills regarding pattern recognition, numerical analysis, and statistics |
| Course application | Übung: https://courses.cs.unibas.ch |
| Language of instruction | English |
| Use of digital media | Online, mandatory |
| Course auditors welcome |
| Interval | Weekday | Time | Room |
|---|
No dates available. Please contact the lecturer.
| Modules |
Doctorate Computer Science: Recommendations (PhD subject: Computer Science) Kernfächer und Seminar (Master's Studies: Computational Biology and Bioinformatics) Modul: Concepts of Machine Intelligence (Master's degree subject: Computer Science) Module: Applications of Distributed Systems (Master's Studies: Computer Science) Module: Concepts of Machine Intelligence (Master's Studies: Computer Science) Module: Interdisciplinary and Transfer of Knowledge (Master's Studies: Actuarial Science) |
| Assessment format | continuous assessment |
| Assessment details | Oral exam Date: 26/27/28 June 2019, office 06.003 |
| Assessment registration/deregistration | Reg.: course registration, dereg: cancel course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,5 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Science, studiendekanat-philnat@unibas.ch |
| Offered by | Fachbereich Informatik |