Глубинное обучение (курс лекций)/2020

Материал из MachineLearning.

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

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

The timetable in Autumn 2020: Fridays, lectures begin at 10-30, seminars begin at 12-15, zoom-link

Lectures and seminars video recordings: link

Anytask invite code: ldQ0L2R

Course chat in Telegram: link

Rules and grades

TBA

Lectures and seminars

Date No. Topic Materials
11 Sep. 2020 1 Introduction. Fully-connected networks.
Matrix calculus, automatic differentiation. Synopsis
18 Sep. 2020 2 Stochastic optimization for neural networks, drop out, batch normalization.
Convolutional neural networks, basic architectures. Presentation
25 Sep. 2020 3 Pytorch and implementation of convolutional neural networks. ipynb 1
ipynb 2

ipynb 3

02 Oct. 2020 4 Semantic image segmentation Presentation (pdf)
Portrait Demo (source)
09 Oct. 2020 5 Object detection Presentation (pdf)
DS Bowl 2018 (pdf)
16 Oct. 2020 6 Neural style transfer. Presentation
23 Oct. 2020 7 Recurrent neural networks. Presentation

Arxiv

2019

2017

2016

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