Deep Learning for Visual Computing Winter School 2017 (DLVCWS 2017)

This repository contains the tutorials for the lab sessions.

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Name		Name	Last commit message	Last commit date
Latest commit History 85 Commits
pytorch_ssim		pytorch_ssim
10_MNIST Digits Classification (LeNet).ipynb		10_MNIST Digits Classification (LeNet).ipynb
11_CIFAR-10 Classification (AlexNet).ipynb		11_CIFAR-10 Classification (AlexNet).ipynb
12_Transfer Learning using a pre-trained Deep Neural Network.ipynb		12_Transfer Learning using a pre-trained Deep Neural Network.ipynb
1_Python for Visual Computing.ipynb		1_Python for Visual Computing.ipynb
2_MNIST Digits Classification (Classical Approach).ipynb		2_MNIST Digits Classification (Classical Approach).ipynb
3_Cifar-10 Classification (Classical Approach).ipynb		3_Cifar-10 Classification (Classical Approach).ipynb
4_PyTorch for Deep Neural Networks.ipynb		4_PyTorch for Deep Neural Networks.ipynb
5_MNIST Digits Classification (Autoencoders).ipynb		5_MNIST Digits Classification (Autoencoders).ipynb
6_CIFAR Classification (Autoencoders).ipynb		6_CIFAR Classification (Autoencoders).ipynb
7_Stacked Denoising and Sparse Autoencoders.ipynb		7_Stacked Denoising and Sparse Autoencoders.ipynb
8_Cost Functions and their Properties.ipynb		8_Cost Functions and their Properties.ipynb
9_Stochastic Gradient Descent and Learning Rate Dynamics.ipynb		9_Stochastic Gradient Descent and Learning Rate Dynamics.ipynb
LICENSE		LICENSE
LeNet-MNIST.ipynb		LeNet-MNIST.ipynb
README.md		README.md
data.zip		data.zip
lecture15.ipynb		lecture15.ipynb
py-demo.py		py-demo.py