머신러닝 토치 라이브러리 강좌 Torch Video Tutorials

Torch Video Tutorials

Light your way in Deep Learning with Torch 

This aims to be a growing collections of introductory video tutorials on the Torch ecosystem. Torch is one of the fastest and most flexible framework existing for Machine and Deep Learning. And yes, flexibility was used to come with an intimidating learning curve... until now.

Enjoy the view of these videos, transcripts and quizes (you can find in the res folder together with some notes about how I made these videos).

1 - Get the basics straight

1.0 - An overview on Lua (slides)

1.1 - An overview on Torch’s Tensors (slides)

1.2 - An overview on Torch’s image package (slides)

2 - Artificial Neural Networks

2.0 - Neural Networks – feed forward (inference) (slides, quiz)

2.1 - Neural Networks – back propagation (training) (slides, quiz)

2.2 - Neural Networks – An overview on Torch’s nn package (slides, script)

3 - Convolutional Neural Networks

3.0 - CNN – Basics (slides, lin, 3conv, 3conv-pool)

3.1 - CNN – Internals (slides, script, 3conv-pool)

3.2 - CNN – Architectures (slides, LeNet5, AlexNet, GoogLeNet)

3.3 - CNN – Training (slides, train.lua)

3.4 - CNN – Loss functions (slides)

4 - Recurrent Neural Networks

4.0 - RNN – Vectors and sequences (slides)

4.1 - RNN – Forward and backward (slides)

4.2 - RNN – nngraph package (slides, script)

4.3 - RNN – Training (slides)

LSTM and training with rnn package coming soon! 

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[출처] https://github.com/Atcold/torch-Video-Tutorials