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31. 微调多层自编码算法 ‎(25 revisions)
32. Neural Networks ‎(23 revisions)
33. 白化 ‎(23 revisions)
34. 自我学习 ‎(23 revisions)
35. Implementing PCA/Whitening ‎(22 revisions)
36. 可视化自编码器训练结果 ‎(22 revisions)
37. Deep Networks: Overview ‎(21 revisions)
38. Self-Taught Learning ‎(21 revisions)
39. 栈式自编码算法 ‎(21 revisions)
40. 稀疏自编码重述 ‎(20 revisions)
41. Exercise:Learning color features with Sparse Autoencoders ‎(19 revisions)
42. Sparse Coding: Autoencoder Interpretation ‎(19 revisions)
43. 梯度检验与高级优化 ‎(19 revisions)
44. Whitening ‎(18 revisions)
45. Self-Taught Learning to Deep Networks ‎(17 revisions)
46. 卷积特征提取 ‎(17 revisions)
47. 矢量化编程 ‎(17 revisions)
48. Neural Network Vectorization ‎(16 revisions)
49. Exercise:Sparse Autoencoder ‎(15 revisions)
50. Backpropagation Algorithm ‎(14 revisions)
51. 实现主成分分析和白化 ‎(14 revisions)
52. Exercise:PCA in 2D ‎(13 revisions)
53. Stacked Autoencoders ‎(13 revisions)
54. Pooling ‎(11 revisions)
55. Using the MNIST Dataset ‎(11 revisions)
56. 稀疏自编码器符号一览表 ‎(11 revisions)
57. 线性解码器 ‎(11 revisions)
58. Exercise:Independent Component Analysis ‎(10 revisions)
59. Independent Component Analysis ‎(10 revisions)
60. Autoencoders and Sparsity ‎(9 revisions)
61. Deriving gradients using the backpropagation idea ‎(9 revisions)
62. Exercise: PCA in 2D ‎(9 revisions)
63. Logistic Regression Vectorization Example ‎(9 revisions)
64. Sparse Coding ‎(9 revisions)
65. Visualizing a Trained Autoencoder ‎(9 revisions)
66. Vectorization ‎(8 revisions)
67. Exercise:Sparse Coding ‎(7 revisions)
68. Gradient checking and advanced optimization ‎(7 revisions)
69. MATLAB Modules ‎(5 revisions)
70. SOFTMAX回归 ‎(5 revisions)
71. UFLDL教程 ‎(5 revisions)
72. Sandbox ‎(4 revisions)
73. Sparse Autoencoder Notation Summary ‎(3 revisions)
74. Visualization with PCA/Whitening ‎(3 revisions)
75. Fminlbfgs Details ‎(2 revisions)
76. Useful Links ‎(2 revisions)

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