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Neural Networks

Courses

https://github.com/Machine-Learning-Tokyo/AI_Curriculum

MIT — MIT 6.S191: Introduction to Deep Learning

http://introtodeeplearning.com/

Playlist

NYU — DS-GA 1008: Deep Learning

https://atcold.github.io/pytorch-Deep-Learning/

Playlist

Stanford — CS231n: Convolutional Neural Networks for Visual Recognition

http://cs231n.stanford.edu/

Stanford — CS236: Deep Generative Models

https://deepgenerativemodels.github.io/

Video recordings are not available but use the syllabus for links to slides.

University of Toronto — CSC2547: Methods in 3D and Geometric Deep Learning

https://www.pair.toronto.edu/csc2547-w21/schedule/

Playlist

Other

Convolution arithmetic

https://github.com/vdumoulin/conv_arithmetic

Batch / instance normalization

Alternatives

Network architectures

  • Squeeze-and-Excitation Networks — Aggregate over the image dimensions, pass the resulting channel values through a feed-forward network, and use the result to scale the original inputs. [Blog post]