UFLDL Tutorial
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Sparse Autoencoder * [[Neural Networks]] * [[Backpropagation Algorithm]] * [[Gradient checking and advanced optimization]] * [[Autoencoders and Sparsity]] * [[Visualizing a Trained Autoencoder]] * [[Sparse Autoencoder Notation Summary]] * [[Exercise:Sparse_Autoencoder]] Vectorized implementation * [[Vectorization]] * [[Logistic Regression Vectorization Example]] * [[Neural Network Vectorization]] * [[Using the MNIST Dataset]] * [[Exercise:Vectorization]] Preprocessing: PCA and Whitening * [[PCA]] * [[Whitening]] * [[Implementing PCA/Whitening]] * [[Exercise: PCA in 2D]] * [[Exercise:PCA and Whitening]] Self-Taught Learning and Unsupervised Feature Learning * [[Unsupervised Feature Learning]] * [[Self-Taught Learning]] * [[Image classification]] (talk about how to extract features from a large image) * [[Softmax Regression]] * [[Exercise:Self-Taught Learning]] Fine-tuning - Exercise: Experiment with and without pre-training Stacked Autoencoders Fine-tuning Stacked AEs Convolutional models (1 layer) Pooling Multiple layers of convolution and pooling '''Advanced Topics''': RBM DBN [[Sparse Coding]] K-means Spatial pyramids?? SFA ICA/TICA/TCNN
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