UFLDL Tutorial
From Ufldl
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sections II, III, IV (up to Logistic Regression) first. | sections II, III, IV (up to Logistic Regression) first. | ||
- | Sparse Autoencoder | + | |
+ | '''Sparse Autoencoder''' | ||
* [[Neural Networks]] | * [[Neural Networks]] | ||
* [[Backpropagation Algorithm]] | * [[Backpropagation Algorithm]] | ||
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- | + | '''Vectorized implementation''' | |
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- | ''' | + | |
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* [[Vectorization]] | * [[Vectorization]] | ||
* [[Logistic Regression Vectorization Example]] | * [[Logistic Regression Vectorization Example]] | ||
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- | Preprocessing: PCA and Whitening | + | '''Preprocessing: PCA and Whitening''' |
* [[PCA]] | * [[PCA]] | ||
* [[Whitening]] | * [[Whitening]] | ||
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- | Softmax Regression | + | '''Softmax Regression''' |
* [[Softmax Regression]] | * [[Softmax Regression]] | ||
* [[Exercise:Softmax Regression]] | * [[Exercise:Softmax Regression]] | ||
- | Self-Taught Learning and Unsupervised Feature Learning | + | '''Self-Taught Learning and Unsupervised Feature Learning''' |
* [[Self-Taught Learning]] | * [[Self-Taught Learning]] | ||
* [[Exercise:Self-Taught Learning]] | * [[Exercise:Self-Taught Learning]] | ||
- | Building Deep Networks for Classification | + | '''Building Deep Networks for Classification''' |
+ | * [[Self-Taught Learning to Deep Networks | From Self-Taught Learning to Deep Networks]] | ||
* [[Deep Networks: Overview]] | * [[Deep Networks: Overview]] | ||
* [[Stacked Autoencoders]] | * [[Stacked Autoencoders]] | ||
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- | Working with Large Images | + | '''Linear Decoders with Autoencoders''' |
+ | * [[Linear Decoders]] | ||
+ | * [[Exercise:Learning color features with Sparse Autoencoders]] | ||
+ | |||
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+ | '''Working with Large Images''' | ||
* [[Feature extraction using convolution]] | * [[Feature extraction using convolution]] | ||
* [[Pooling]] | * [[Pooling]] | ||
- | * [[ | + | * [[Exercise:Convolution and Pooling]] |
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---- | ---- | ||
+ | '''Note''': The sections above this line are stable. The sections below are still under construction, and may change without notice. Feel free to browse around however, and feedback/suggestions are welcome. | ||
+ | |||
+ | '''Miscellaneous''' | ||
+ | * [[MATLAB Modules]] | ||
+ | * [[Style Guide]] | ||
+ | * [[Useful Links]] | ||
+ | '''Miscellaneous Topics''' | ||
+ | * [[Data Preprocessing]] | ||
+ | * [[Deriving gradients using the backpropagation idea]] | ||
'''Advanced Topics''': | '''Advanced Topics''': | ||
- | [[ | + | '''Sparse Coding''' |
+ | * [[Sparse Coding]] | ||
+ | * [[Sparse Coding: Autoencoder Interpretation]] | ||
+ | * [[Exercise:Sparse Coding]] | ||
- | [[ | + | '''ICA Style Models''' |
+ | * [[Independent Component Analysis]] | ||
+ | * [[Exercise:Independent Component Analysis]] | ||
- | [[Denoising Autoencoders]] | + | '''Others''' |
+ | * [[Convolutional training]] | ||
+ | * [[Restricted Boltzmann Machines]] | ||
+ | * [[Deep Belief Networks]] | ||
+ | * [[Denoising Autoencoders]] | ||
+ | * [[K-means]] | ||
+ | * [[Spatial pyramids / Multiscale]] | ||
+ | * [[Slow Feature Analysis]] | ||
+ | * [[Tiled Convolution Networks]] | ||
- | + | ---- | |
- | + | Material contributed by: Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen | |
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- | + | {{Languages|UFLDL教程|中文}} |