/UFLDL_Ex

Complete codes for exercises in Stanford UFLDL tutorials.

UFLDL_Ex

Contents

Complete codes for exercises in Stanford UFLDL tutorials.

  1. http://ufldl.stanford.edu/tutorial/index.php/UFLDL_Tutorial
  2. http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial

Exs

  1. Linear regression, logistic regression, and softmax regression
  2. Multilayer supervised neural network
  3. Convolutional neural network
  4. Sparse autoencoder
  5. PCA whitening, and RICA
  6. Self-taught learning
  7. Stacked autoencoders
  8. Linear decoder

PS. Listed in the order of finishing time.

Notes

  1. Some datasets needed are not included for the sake of size. You can download them yourself on the tutorial website. (Some are included in the exercise .zip file downloaded from the website)

  2. The code style is bad, but should be right :). So this may just serve as a reference when you are going through the tutorials.

  3. The code is written with help of many references. If you have any questions or find any mistakes, feel free to contact me.

  4. Thank Andrew Ng so much for the wonderful tutorial!

References

  1. http://www.cnblogs.com/tornadomeet/tag/Deep%20Learning/
  2. http://yann.lecun.com/exdb/mnist/
  3. http://cogprints.org/5869/1/cnn_tutorial.pdf
  4. https://github.com/rasmusbergpalm/DeepLearnToolbox
  5. Many others...

Author

Derek Yang

yb.derek@gmail.com

2014.1.24