| Detailed information |
| Original study plan |
Bachelor's programme Bioinformatics 2015W |
| Objectives |
This practical course complements the lecture "Machine Learning: Supervised Techniques" and aims at practicing the concepts and methods acquired in the lecture.
|
| Subject |
- Basics of classification and regression
- Evaluation of machine learning results (confusion matrices, ROC)
- Under- and overfitting / bias and variance
- Cross-validation and hyperparameter selection
- Logistic regression
- Support vector machines and kernels
- Neural networks and deep networks
- Time series (sequence) analysis
- Bagging and boosting
- Feature selection and feature construction
|
| Criteria for evaluation |
Marking is based on homework
|
| Methods |
Students are given assignments in 1-2 week intervals. Homework must be handed in. Results are to be presented and discussed in the course.
|
| Language |
English |
| Study material |
Assignments and homework submissions are managed via JKU Moodle.
Where necessary, complimentary course material is provided for download.
|
| Changing subject? |
No |
| Corresponding lecture |
in collaboration with 875BIN2MUTU13: UE Machine Learning: Unsupervised Techniques (1,5 ECTS) equivalent to
875BIN2TMLU12: UE Theoretical Bioinformatics and Machine Learning (3 ECTS) -or- BIMPHUEBIN2: UE Bioinformatik II: Theoretische Bioinformatik und Maschinelles Lernen (3 ECTS)
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