There will be two main types of seminars within the course:
There are also a midterm test and oral presentations of the assignment results planned on certain weeks.
Students use a development platform of their choice to implement the programs for their assignment (typically C/C++, Java, Matlab or Mathematica).
An expected average home preparation time is 5 hours per week.
| Seminar | Date | Topic | Materials |
|---|---|---|---|
| 1. | 25.2. | Survey of successful applications of neural networks | ann_examples-2016.pdf |
| 2. | 3.3. | Data mining | JavaNNS, JavaNNS (Win), data.zip, JavaNNS (Mac), snnsv4.2.manual.pdf, Quick Guide to javaNNS RapidMiner RapidMiner download Glass data Three-way data splits |
| 3. | 10.3. | Successful applications of evolutionary algorithms, EA individual project assignment | applications_of_eas_2015.pdf, individual_projects_ea_2016.pdf, individual projects ANNs |
| 4. | 17.3. | Evolutionary models (steady-state, generational, etc.) (Java) | CheatSheet, sga_source_codes.zip, solution |
| 5. | 24.3. | Consultations on assignment, implementing MLP evaluation and back-propagation learning (Java) | Cheatsheet, Cheatsheet2, Sources, solution |
| 6. | 31.3. | Evolutionary algorithms: implementing and testing crossover/mutation operators (Java) | Sources, Cheatsheet, Solution, TSP references |
| 7. | 7.4. | Consultations on assignment | |
| 8. | 14.4. | Recurrent ANNs: synchronous/asynchronous evaluation (Java) | Cheatsheet, Sources |
| 9. | 21.4. | Consultations on assignment | |
| 10. | 28.4. | Midterm test. | example test, Test results |
| 11. | 5.5. | Consultations on assignment | |
| 12. | 12.5. | multiobjective optimization: NSGA (Java) | Sources, cheatsheet_nsga2.pdf |
| 13. | 19.5. | Deadline for the program implementation, presentations of the program implementations | |
| 14. | 26.5. | Deadline for the report submission, presentations of the program implementations, Credits |