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| Course program:
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| https://www.hse.ru/data/2018/06/05/1150113338/program-2129241367-JndYcQjSAq.pdf
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| Grading:
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| Final grade = 50% online course + 20% test + 30% homework
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| Оценки:
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| Additional project:
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| Homework with Kaggle competition: https://docs.google.com/document/d/1kTMYq21UFqZOqftjKAPq8G7RRkO7kX3MomsVIVhW830/edit?usp=sharing
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| Release date:
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| Deadline:
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| Exam:
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| In writing, theoretical questions, for instance:
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| SGD variations: Moment, RMSProp, Adam with explanation
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| Description of backprop and proof of its efficiency (линейное время работы)
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| Gradient of a dense layer in matrix notation (with proof)
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| Typical CNN architecture, purpose of each layer, how to do backprop
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| Inception V3 architecture choices
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| Description of auto-encoder, application to images
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| Gradient of RNN cell (with proof)
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| Семинары:
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| 1. Keras Tutorial https://colab.research.google.com/drive/1HoEsK580KAzMGuvFyYwUFdnRzuZ_hC13
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Текущая версия от 10:49, 18 февраля 2020