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  1. 主成分分析 ‎(65 revisions)
  2. UFLDL Tutorial ‎(61 revisions)
  3. 稀疏编码自编码表达 ‎(58 revisions)
  4. Softmax Regression ‎(56 revisions)
  5. Exercise:Convolution and Pooling ‎(53 revisions)
  6. 神经网络 ‎(53 revisions)
  7. 反向传导算法 ‎(52 revisions)
  8. 稀疏编码 ‎(48 revisions)
  9. Exercise:Softmax Regression ‎(46 revisions)
  10. Feature extraction using convolution ‎(45 revisions)
  11. 神经网络向量化 ‎(44 revisions)
  12. PCA ‎(43 revisions)
  13. Exercise:Vectorization ‎(39 revisions)
  14. Exercise:Self-Taught Learning ‎(38 revisions)
  15. 数据预处理 ‎(38 revisions)
  16. Exercise:PCA and Whitening ‎(37 revisions)
  17. Main Page ‎(36 revisions)
  18. 自编码算法与稀疏性 ‎(35 revisions)
  19. Softmax回归 ‎(34 revisions)
  20. 池化 ‎(34 revisions)
  21. Linear Decoders ‎(32 revisions)
  22. 深度网络概览 ‎(32 revisions)
  23. UFLDL Recommended Readings ‎(31 revisions)
  24. 逻辑回归的向量化实现样例 ‎(30 revisions)
  25. 用反向传导思想求导 ‎(29 revisions)
  26. Fine-tuning Stacked AEs ‎(28 revisions)
  27. 独立成分分析 ‎(27 revisions)
  28. Data Preprocessing ‎(26 revisions)
  29. Exercise: Implement deep networks for digit classification ‎(25 revisions)
  30. 从自我学习到深层网络 ‎(25 revisions)
  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)

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