UFLDL Tutorial
From Ufldl
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* [[Exercise:PCA in 2D]] | * [[Exercise:PCA in 2D]] | ||
* [[Exercise:PCA and Whitening]] | * [[Exercise:PCA and Whitening]] | ||
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+ | Softmax Regression | ||
+ | * [[Softmax Regression]] | ||
+ | * [[Exercise:Softmax Regression]] | ||
Self-Taught Learning and Unsupervised Feature Learning | Self-Taught Learning and Unsupervised Feature Learning | ||
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* [[Self-Taught Learning]] | * [[Self-Taught Learning]] | ||
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* [[Exercise:Self-Taught Learning]] | * [[Exercise:Self-Taught Learning]] | ||
Building Deep Networks for Classification | Building Deep Networks for Classification | ||
- | * [[ | + | * [[Stacked Autoencoders]] |
- | * [[Exercise: | + | * [[Fine-tuning Stacked AEs]] |
+ | * [[Exercise: Implement deep networks for digit classification]] | ||
- | + | Working with Large Images | |
- | + | * Feature extraction using convolution | |
+ | * Pooling | ||
+ | * Multiple layers of convolution and pooling | ||
- | + | '''Advanced Topics''': | |
- | + | [[Restricted Boltzmann Machines]] | |
- | + | [[Deep Belief Networks]] | |
- | + | [[Sparse Coding]] | |
- | + | [[K-means]] | |
- | + | [[Spatial pyramids / Multiscale]] | |
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- | [[ | + | |
- | + | [[Slow Feature Analysis]] | |
- | + | ICA Style Models: | |
+ | * [[Independent Component Analysis]] | ||
+ | * [[Topographic Independent Component Analysis]] | ||
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- | + | [[Tiled Convolution Networks]] |