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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
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1 |
Introduction and Overview |
Reading the related documents |
Presentation |
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2 |
Computational Learning Theory |
Reading the related documents |
Presentation |
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3 |
Support Vector Machines I |
Reading the related documents |
Presentation |
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4 |
Support Vector Machines II |
Reading the related documents |
Presentation |
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5 |
Clustering |
Reading the related documents |
Presentation |
|
6 |
Manifold Learning I (non-linear dimensionality reduction) |
Reading the related documents |
Presentation |
|
7 |
Manifold Learning II |
Reading the related documents |
Presentation |
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8 |
Midterm Exam |
Studying of the previous topics |
Exam |
|
9 |
Ensembles |
Reading the related documents |
Presentation |
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10 |
Recurrent Neural Networks I |
Reading the related documents |
Presentation |
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11 |
Recurrent Neural Networks II |
Reading the related documents |
Presentation |
|
12 |
Spiking Neural Networks |
Reading the related documents |
Presentation |
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13 |
Hybrid Systems |
Reading the related documents |
Presentation |
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14 |
Presentations I |
Preparation of presentations |
Presentation |
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15 |
Presentations II |
Preparation of presentations |
Presentation |
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16/17 |
Final Exam |
Studying of the topics included in the course and student presentations |
Exam |
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