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- 神经网络 (12:34, 7 April 2013)
- Gradient checking and advanced optimization (12:40, 7 April 2013)
- Autoencoders and Sparsity (12:43, 7 April 2013)
- Sparse Autoencoder Notation Summary (12:45, 7 April 2013)
- Visualizing a Trained Autoencoder (12:49, 7 April 2013)
- Backpropagation Algorithm (12:50, 7 April 2013)
- Vectorization (13:07, 7 April 2013)
- Logistic Regression Vectorization Example (13:09, 7 April 2013)
- Neural Network Vectorization (13:13, 7 April 2013)
- PCA (13:18, 7 April 2013)
- Whitening (13:20, 7 April 2013)
- Implementing PCA/Whitening (13:22, 7 April 2013)
- Softmax Regression (13:24, 7 April 2013)
- Self-Taught Learning (13:26, 7 April 2013)
- Self-Taught Learning to Deep Networks (13:29, 7 April 2013)
- Deep Networks: Overview (13:31, 7 April 2013)
- Stacked Autoencoders (13:33, 7 April 2013)
- UFLDL Tutorial (18:22, 7 April 2013)
- Fine-tuning Stacked AEs (04:04, 8 April 2013)
- Linear Decoders (04:06, 8 April 2013)
