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neural_nets_larochelle

  • 收录时间:2018-03-19 01:27:44
  • 文件大小:6GB
  • 下载次数:241
  • 最近下载:2021-01-11 14:39:00
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文件列表

  1. Neural networks [3.10] - Conditional random fields - belief propagation--z5lKPHcumo.mp4 200MB
  2. Neural networks [6.4] - Autoencoder - linear autoencoder-xq-I0Rl8mt0.mp4 159MB
  3. Neural networks [3.4] - Conditional random fields - computing the partition function-fGdXkVv1qNQ.mp4 136MB
  4. Neural networks [7.9] - Deep learning - DBN pre-training-35MUlYCColk.mp4 134MB
  5. Neural networks [10.10] - Natural language processing - multitask learning-ciNBQupWsAc.mp4 130MB
  6. Neural networks [2.11] - Training neural networks - optimization-Bver7Ttgb9M.mp4 120MB
  7. Neural networks [6.6] - Autoencoder - denoising autoencoder-t2NQ_c5BFOc.mp4 118MB
  8. Neural networks [9.8] - Computer vision - example-Gk8VvSL3IMk.mp4 118MB
  9. Neural networks [10.7] - Natural language processing - hierarchical output layer-B95LTf2rVWM.mp4 112MB
  10. Neural networks [9.6] - Computer vision - convolutional network-cDdpwAIsuD8.mp4 111MB
  11. Neural networks [1.6] - Feedforward neural network - biological inspiration-cuJ4IC5_pGs.mp4 111MB
  12. Neural networks [10.6] - Natural language processing - neural network language model-FoDz01QNSiY.mp4 104MB
  13. Neural networks [10.9] - Natural language processing - convolutional network-6jCDUQ-e-fY.mp4 104MB
  14. Neural networks [2.4] - Training neural networks - hidden layer gradient-xFhM_Kwqw48.mp4 99MB
  15. Neural networks [3.6] - Conditional random fields - performing classification-pQJvX9U-MyE.mp4 98MB
  16. Neural networks [5.1] - Restricted Boltzmann machine - definition-p4Vh_zMw-HQ.mp4 97MB
  17. Neural networks [10.13] - Natural language processing - tree inference-NJozqoejJnA.mp4 96MB
  18. Neural networks [7.1] - Deep learning - motivation-vXMpKYRhpmI.mp4 96MB
  19. Neural networks [7.7] - Deep learning - deep belief network-vkb6AWYXZ5I.mp4 95MB
  20. Neural networks [2.7] - Training neural networks - backpropagation-_KoWTD8T45Q.mp4 92MB
  21. Neural networks [10.8] - Natural language processing - word tagging-pCLIo4Z-PsM.mp4 88MB
  22. Neural networks [7.8] - Deep learning - variational bound-pStDscJh2Wo.mp4 85MB
  23. Neural networks [10.14] - Natural language processing - recursive network training-oRxgRHJztPI.mp4 83MB
  24. Neural networks [7.3] - Deep learning - unsupervised pre-training-Oq38pINmddk.mp4 82MB
  25. Neural networks [9.4] - Computer vision - discrete convolution-Y7TMwqAWEdo.mp4 82MB
  26. Neural networks [7.4] - Deep learning - example-SXnG-lQ7RJo.mp4 82MB
  27. Neural networks [5.4] - Restricted Boltzmann machine - contrastive divergence-MD8qXWucJBY.mp4 79MB
  28. Neural networks [9.3] - Computer vision - parameter sharing-aAT1t9p7ShM.mp4 79MB
  29. Neural networks [8.4] - Sparse coding - dictionary update with block-coordinate descent-UMdNfhgPKTc.mp4 79MB
  30. Neural networks [2.8] - Training neural networks - regularization-JfkbyODyujw.mp4 78MB
  31. Neural networks [3.3] - Conditional random fields - context window-G4lnHc2M1CA.mp4 74MB
  32. Neural networks [8.6] - Sparse coding - online dictionary learning algorithm-IePxTepLvQc.mp4 74MB
  33. Neural networks [5.2] - Restricted Boltzmann machine - inference-lekCh_i32iE.mp4 73MB
  34. Neural networks [4.2] - Training CRFs - unary log-factor gradient-fU2W7KRoS2U.mp4 72MB
  35. Neural networks [4.5] - Training CRFs - maximum-entropy Markov model-aMi2xnYEwbc.mp4 71MB
  36. Neural networks [6.7] - Autoencoder - contractive autoencoder-79sYlJ8Cvlc.mp4 71MB
  37. Neural networks [3.7] - Conditional random fields - factors, sufficient statistics and linear CRF-uXV2an9TdJY.mp4 70MB
  38. Neural networks [6.2] - Autoencoder - loss function-xTU79Zs4XKY.mp4 70MB
  39. Neural networks [8.2] - Sparse coding - inference (ISTA algorithm)-L6qhzWWtqQs.mp4 70MB
  40. Neural networks [7.2] - Deep learning - difficulty of training-YoiUlN_77LU.mp4 69MB
  41. Neural networks [3.8] - Conditional random fields - Markov network-ZYUnyyVgtyA.mp4 68MB
  42. Neural networks [10.4] - Natural language processing - word representations-PKszi8iogak.mp4 68MB
  43. Neural networks [9.10] - Computer vision - convolutional RBM-y0SISi_T6s8.mp4 68MB
  44. Neural networks [9.7] - Computer vision - object recognition-eU83LSM3xnk.mp4 66MB
  45. Neural networks [2.10] - Training neural networks - model selection-Fs-raHUnF2M.mp4 66MB
  46. Neural networks [8.8] - Sparse coding - feature extraction-FL81zSjAEEg.mp4 66MB
  47. Neural networks [2.1] - Training neural networks - empirical risk minimization-5adNQvSlF50.mp4 66MB
  48. Neural networks [8.1] - Sparse coding - definition-7a0_iEruGoM.mp4 66MB
  49. Neural networks [7.6] - Deep learning - deep autoencoder-z5ZYm_wJ37c.mp4 63MB
  50. Neural networks [5.5] - Restricted Boltzmann machine - contrastive divergence (parameter update)-wMb7cads0go.mp4 62MB
  51. Neural networks [5.3] - Restricted Boltzmann machine - free energy-e0Ts_7Y6hZU.mp4 62MB
  52. Neural networks [3.2] - Conditional random fields - linear chain CRF-PGBlyKtfB74.mp4 59MB
  53. Neural networks [10.2] - Natural language processing - preprocessing-jcrhYEYwO9k.mp4 58MB
  54. Neural networks [1.1] - Feedforward neural network - artificial neuron-SGZ6BttHMPw.mp4 56MB
  55. Neural networks [7.5] - Deep learning - dropout-UcKPdAM8cnI.mp4 56MB
  56. Neural networks [3.5] - Conditional random fields - computing marginals-hjkwp-eDwt8.mp4 55MB
  57. Neural networks [10.5] - Natural language processing - language modeling-iGmHnICXDss.mp4 55MB
  58. Neural networks [4.4] - Training CRFs - discriminative vs. generative learning-MD4mY3Zj5E4.mp4 54MB
  59. Neural networks [5.8] - Restricted Boltzmann machine - extensions-iPuqoQih9xk.mp4 53MB
  60. Neural networks [4.7] - Training CRFs - general conditional random field-QY9k7tJistU.mp4 52MB
  61. Neural networks [5.7] - Restricted Boltzmann machine - example-n26NdEtma8U.mp4 51MB
  62. Neural networks [9.5] - Computer vision - pooling and subsampling-I-JKxcpbRT4.mp4 50MB
  63. Neural networks [10.3] - Natural language processing - one-hot encoding-iZ3e_cifP7Y.mp4 50MB
  64. Neural networks [9.9] - Computer vision - data set expansion-Km1Q5VcSKAg.mp4 49MB
  65. Neural networks [2.9] - Training neural networks - parameter initialization-sLfogkzFNfc.mp4 49MB
  66. Neural networks [8.7] - Sparse coding - ZCA preprocessing-eUiwhV1QcQ4.mp4 48MB
  67. Neural networks [10.11] - Natural language processing - recursive network-AqEF2HIMjYA.mp4 48MB
  68. Neural networks [8.9] - relationship with V1-MdomgSiL86Q.mp4 47MB
  69. Neural networks [4.3] - Training CRFs - pairwise log-factor gradient-1W2lkcGV2Zo.mp4 47MB
  70. Neural networks [6.5] - Autoencoder - undercomplete vs. overcomplete hidden layer-5rLgoM2Pkso.mp4 46MB
  71. Neural networks [1.4] - Feedforward neural network - multilayer neural network-apPiZd-qnZ8.mp4 46MB
  72. Neural networks [8.5] - Sparse coding - dictionary learning algorithm-PzNMff7cYjM.mp4 45MB
  73. Neural networks [9.1] - Computer vision - motivation-rxKrCa4bg1I.mp4 45MB
  74. Neural networks [2.3] - Training neural networks - output layer gradient-1N837i4s1T8.mp4 44MB
  75. Neural networks [5.6] - Restricted Boltzmann machine - persistent CD-S0kFFiHzR8M.mp4 42MB
  76. Neural networks [1.2] - Feedforward neural network - activation function-tCHIkgWZLOQ.mp4 42MB
  77. Neural networks [4.8] - Training CRFs - pseudolikelihood-ltRT1m7vaBU.mp4 42MB
  78. Neural networks [3.9] - Conditional random fields - factor graph-Q5GTCHVsHXY.mp4 41MB
  79. Neural networks [6.1] - Autoencoder - definition-FzS3tMl4Nsc.mp4 37MB
  80. Neural networks [4.6] - Training CRFs - hidden Markov model-jdlJfM707MM.mp4 35MB
  81. Neural networks [4.1] - Training CRFs - loss function-6dpGB60Q1Ts.mp4 34MB
  82. Neural networks [2.6] - Training neural networks - parameter gradient-p5tL2JqCRDo.mp4 31MB
  83. Neural networks [10.12] - Natural language processing - merging representations-gPNPINa7PaM.mp4 30MB
  84. Neural networks [9.2] - Computer vision - local connectivity-vLf3KVe2Z1k.mp4 29MB
  85. Neural networks [2.2] - Training neural networks - loss function-PpFTODTztsU.mp4 29MB
  86. Neural networks [3.1] - Conditional random fields - motivation-GF3iSJkgPbA.mp4 27MB
  87. Neural networks [1.5] - Feedforward neural network - capacity of neural network-O4I7dQC4VtU.mp4 27MB
  88. Neural networks [2.5] - Training neural networks - activation function derivative-tf9p1xQbWNM.mp4 23MB
  89. Neural networks [1.3] - Feedforward neural network - capacity of single neuron-iT5P4z6Fzj8.mp4 23MB
  90. Neural networks [8.3] - Sparse coding - dictionary update with projected gradient descent-bhqNSjJ_A20.mp4 22MB
  91. Neural networks [10.1] - Natural language processing - motivation-OzZIOiMVUyM.mp4 19MB
  92. Neural networks [6.3] - Autoencoder - example-6DO_jVbDP3I.mp4 18MB