UFLDL Tutorial

From Ufldl

Jump to: navigation, search
 
Line 4: Line 4:
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]]
Line 14: Line 15:
-
Vectorized implementation
+
'''Vectorized implementation'''
* [[Vectorization]]
* [[Vectorization]]
* [[Logistic Regression Vectorization Example]]
* [[Logistic Regression Vectorization Example]]
* [[Neural Network Vectorization]]
* [[Neural Network Vectorization]]
-
* [[Using the MNIST Dataset]]
 
* [[Exercise:Vectorization]]
* [[Exercise:Vectorization]]
-
Preprocessing: PCA and Whitening
+
'''Preprocessing: PCA and Whitening'''
* [[PCA]]
* [[PCA]]
* [[Whitening]]
* [[Whitening]]
Line 30: Line 30:
-
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]]
Line 47: Line 48:
-
Working with Large Images
+
'''Linear Decoders with Autoencoders'''
 +
* [[Linear Decoders]]
 +
* [[Exercise:Learning color features with Sparse Autoencoders]]
 +
 
 +
 
 +
'''Working with Large Images'''
* [[Feature extraction using convolution]]
* [[Feature extraction using convolution]]
* [[Pooling]]
* [[Pooling]]
-
* [[Multiple layers of convolution and pooling]]
+
* [[Exercise:Convolution and Pooling]]
-
 
+
----
----
 +
'''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''':
-
[[Restricted Boltzmann Machines]]
+
'''Sparse Coding'''
 +
* [[Sparse Coding]]
 +
* [[Sparse Coding: Autoencoder Interpretation]]
 +
* [[Exercise:Sparse Coding]]
-
[[Deep Belief Networks]]
+
'''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]]
-
[[Sparse Coding]]
+
----
-
[[K-means]]
+
Material contributed by: Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen
-
 
+
-
[[Spatial pyramids / Multiscale]]
+
-
 
+
-
[[Slow Feature Analysis]]
+
-
 
+
-
ICA Style Models:
+
-
* [[Independent Component Analysis]]
+
-
* [[Topographic Independent Component Analysis]]
+
-
[[Tiled Convolution Networks]]
 
-
[[Code]]
+
{{Languages|UFLDL教程|中文}}

Latest revision as of 18:22, 7 April 2013

Personal tools