Глубинное обучение (курс лекций)/2019

Материал из MachineLearning.

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Версия 11:20, 14 февраля 2019

This is introductory course on deep learning models and their application for solving different problems of image and text analysis.

Instructors: Dmitry Kropotov, Victor Kitov, Nadezhda Chirkova, Oleg Ivanov and Evgeny Nizhibitsky.

E-mail for questions: bayesml@gmail.com. Please include in subject the tag [CMC DL19].

The timetable in Spring 2019: Fridays, room 685, lectures begin at 14-35, seminars begin at 16-20.

Announcements

Rules and grades

Practical assignments

Practical assignments are provided on course page in anytask.org. Invite code: ????

Lectures

Date	No.	Topic	Materials
15 Feb. 2019	1	Introduction. Automatic differentiation.
22 Feb. 2019	2	Optimization and regularization methods for neural networks
01 Mar. 2019	3	Convolutional neural networks for image classification problem
15 Mar. 2019	4	Convolutional neural networks for image segmentation problem
22 Mar. 2019	5	Object detection and localization on images
29 Mar. 2019	6	Image style transfer
05 Apr. 2019	7	Recurrent neural networks
12 Apr. 2019	8	Attention mechanism
19 Apr. 2019	9	Generative adversarial networks
26 Apr. 2019	10	Riemannian optimization
17 May 2019	11

Seminars

Date	No.	Topic	Materials
15 Feb. 2019	1	Automatic differentiation.
22 Feb. 2019	2	Introduction to Azure and Pytorch
01 Mar. 2019	3	Convolutional neural networks for MNIST
15 Mar. 2019	4	Deep learning contests
22 Mar. 2019	5	Face recognition
29 Mar. 2019	6	Image style transfer
05 Apr. 2019	7	Recurrent neural networks
12 Apr. 2019	8	Attention mechanism
19 Apr. 2019	9	Generative adversarial networks
26 Apr. 2019	10	Riemannian optimization
17 May 2019	11

Arxiv

2017

2016