Machine Learning
| Registration | Click here to enroll in this course |
|---|---|
| Instructors | Stefan Kramer, Prof. Dr., Jörg Wicker, Dipl.-Bioinf., Michael Geilke, M.Sc. |
| Time | Thursday, 16:00–18:00 |
| Recurrence | weekly from Apr 19, 2012 until Jul 21, 2012 |
| First session | Apr 19, 2012 04:00 PM |
| Location | 03-428 |
| Language of instruction | German |
| Credits | 6 |
| Directory | Link to the directory entry for this lecture |
- Note:
- This course requires registration .
Contact
If there are any questions or comments regarding the lecture, the tutorials or exercise sheets, please write an email to
teaching-infosys@lists.uni-mainz.de
News
- First tutorial (April 23rd) takes place in room 03-620 (M/I 2).
Topics
- decision trees: representation, learning, overfitting, pruning
- ensembles: boosting, bagging, stacking, random forests
- linear models: linear regression, ridge regression, logistic regression
- neural networks: perceptron, multi-layer perceptron, back propagation
- instance-based learning: k-NN, locally weighted learning, RBF networks, case-based reasoning
- SVMs: margins, kernels
- relational learning, inductive logic programming
- reinforcement learning
- genetic algorithms
Tutorials and Exercise Sheets
There is one tutorial for the lecture:
| Day | Time | Room |
|---|---|---|
| Monday |
14:00-16:00 |
04-224 |
Exercise sheets will be published on the lecture's website on Thursday at 19:00. Solutions can be handed in in German or English and have to be submitted in groups of 2 students at 12:00 the following Thursday. The submissions have to be posted in the exercise box "Machine Learning" in room 05-230. On the solution the names of all students are required as well as their email address. The sheets will be corrected and handed out in the tutorials. Participation in the tutorials is mandatory.
There will be no tutorial in the first week, the first date is Monday , April 23. The password to download the sheets will be given in the first lecture.
Final Exam
Admission to the final exam is granted if
- 50 % of all points in the exercise sheets are achieved,
- all tutorials have been attended (being absent with excuse is allowed once),
- and the student is registered at Jogustine on time.
Literature
Pattern recognition and machine learning
Author: Christopher M. Bishop
ISBN: 0-387-31073-8 ; 978-0-387-31073-2
PMC: ST 3000 BIS1
Data mining : concepts and techniques
Author: Jiawei Han, Micheline Kamber
ISBN: 1-55860-489-8
PMC: 10/DATENBANKEN ST 5300 HAN2
Machine Learning
Author: Tom Mitchell
ISBN: 0-07-115467-1 ; 0-07-042807-7 ; 978-0-07-115467-3
PMC: ST 1300 MIT1
