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Building Machine Learning Systems with TensorFlow [Video]

  • 收录时间:2018-03-11 22:18:27
  • 文件大小:1GB
  • 下载次数:266
  • 最近下载:2021-01-20 02:28:29
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文件列表

  1. Code/Section 8/imagenet-vgg-verydeep-19.mat 549MB
  2. 7.5-Writing Music a la Bach - Building Machine Learning Systems with TensorFlow [Video].mp4 30MB
  3. 1.4-Basic Tensor Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 30MB
  4. Code/Section 6/data/cifar-10-batches-bin/data_batch_1.bin 29MB
  5. Code/Section 6/data/cifar-10-batches-bin/test_batch.bin 29MB
  6. 4.3-Univariate Logistic Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 25MB
  7. 1.2-TensorFlows Main Data Structure – Tensors - Building Machine Learning Systems with TensorFlow [Video].mp4 20MB
  8. 3.4-Multivariate Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 19MB
  9. 1.5-How TensorBoard Works - Building Machine Learning Systems with TensorFlow [Video].mp4 19MB
  10. 3.3-Univariate Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 19MB
  11. 2.4-Project 1 – k-Means Clustering on Synthetic Datasets - Building Machine Learning Systems with TensorFlow [Video].mp4 16MB
  12. 1.6-Reading Information from Disk - Building Machine Learning Systems with TensorFlow [Video].mp4 16MB
  13. 2.3-k-Nearest Neighbor - Building Machine Learning Systems with TensorFlow [Video].mp4 15MB
  14. 6.2-Applying Convolution in TensorFlow - Building Machine Learning Systems with TensorFlow [Video].mp4 15MB
  15. 1.3-Handling the Computing Workflow – TensorFlows Data Flow Graph - Building Machine Learning Systems with TensorFlow [Video].mp4 14MB
  16. 5.1-Preliminary Concepts - Building Machine Learning Systems with TensorFlow [Video].mp4 14MB
  17. 6.6-MNIST Digit Classification - Building Machine Learning Systems with TensorFlow [Video].mp4 14MB
  18. 5.3-Second Project – Modeling Cars Fuel Efficiency with Non-Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 14MB
  19. 1.1-The course Overview - Building Machine Learning Systems with TensorFlow [Video].mp4 13MB
  20. 8.5-Painting with Style – VGG Style Transfer - Building Machine Learning Systems with TensorFlow [Video].mp4 12MB
  21. 5.4-Third Project – Learning to Classify Wines Multiclass Classification - Building Machine Learning Systems with TensorFlow [Video].mp4 11MB
  22. 7.4-Univariate Time Series Prediction with Energy Consumption Data - Building Machine Learning Systems with TensorFlow [Video].mp4 11MB
  23. 5.2-First Project – Non-Linear Synthetic Function Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 11MB
  24. 6.7-Image Classification with the CIFAR10 Dataset - Building Machine Learning Systems with TensorFlow [Video].mp4 10MB
  25. 9.2-MacOS Installation - Building Machine Learning Systems with TensorFlow [Video].mp4 10MB
  26. 4.4-Univariate Logistic Regression with keras - Building Machine Learning Systems with TensorFlow [Video].mp4 10MB
  27. 4.2-The Logistic Function - Building Machine Learning Systems with TensorFlow [Video].mp4 10MB
  28. 9.1-Windows Installation - Building Machine Learning Systems with TensorFlow [Video].mp4 10MB
  29. 3.1-Univariate Linear Modelling Function - Building Machine Learning Systems with TensorFlow [Video].mp4 9MB
  30. 6.3-Subsampling Operation –Pooling - Building Machine Learning Systems with TensorFlow [Video].mp4 9MB
  31. 8.2-Alexnet - Building Machine Learning Systems with TensorFlow [Video].mp4 9MB
  32. 2.5-Project 2 – Nearest Neighbor on Synthetic Datasets - Building Machine Learning Systems with TensorFlow [Video].mp4 8MB
  33. 7.2-AFundamental Component – Gate Operation and Its Steps - Building Machine Learning Systems with TensorFlow [Video].mp4 8MB
  34. 4.1-Logistic Function Predecessor – The Logit Functions - Building Machine Learning Systems with TensorFlow [Video].mp4 7MB
  35. 6.1-Origin of Convolutional Neural Networks - Building Machine Learning Systems with TensorFlow [Video].mp4 7MB
  36. 7.1-Recurrent Neural Networks - Building Machine Learning Systems with TensorFlow [Video].mp4 7MB
  37. 2.2-Mechanics of k-Means - Building Machine Learning Systems with TensorFlow [Video].mp4 7MB
  38. 3.2-Optimizer Methods in TensorFlow – The Train Module - Building Machine Learning Systems with TensorFlow [Video].mp4 6MB
  39. 6.4-Improving Efficiency – Dropout Operation - Building Machine Learning Systems with TensorFlow [Video].mp4 6MB
  40. 8.1-Deep Neural Network Definition and Architectures Through Time - Building Machine Learning Systems with TensorFlow [Video].mp4 5MB
  41. 2.1-Learning from Data –Unsupervised Learning - Building Machine Learning Systems with TensorFlow [Video].mp4 5MB
  42. 7.3-TensorFlow LSTM Useful Classes and Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 4MB
  43. 8.4-Residual Networks (ResNet) - Building Machine Learning Systems with TensorFlow [Video].mp4 4MB
  44. Code/Section 1/Section1.ipynb 3MB
  45. Code/Section 1/.ipynb_checkpoints/Section1-checkpoint.ipynb 3MB
  46. 6.5-Convolutional Type Layer Building Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 3MB
  47. Code/Section 7/Code/data/elec_load.csv 2MB
  48. 8.3-Inception V3 - Building Machine Learning Systems with TensorFlow [Video].mp4 2MB
  49. Code/Section 2/Section2.ipynb 707KB
  50. Code/Section 6/data/blue_jay.jpg 606KB
  51. Code/Section 8/style.jpg 245KB
  52. Code/Section 8/content.jpg 181KB
  53. Code/Section 7/Code/CH7_time_series.ipynb 150KB
  54. Code/Section 6/data/leopard.jpg 143KB
  55. Code/Section 3/Section3.ipynb 108KB
  56. Code/Section 5/CH5_Nonlinear.ipynb 102KB
  57. Code/Section 6/data/test2.gif 102KB
  58. Code/Section 6/data/test.gif 95KB
  59. Code/Section 6/CH6_Mnist_final.ipynb 86KB
  60. Code/Section 4/CH4_Univariate_logistic_regression.ipynb 56KB
  61. Code/Section 7/Code/model.py 56KB
  62. Code/Section 7/Code/utils.py 53KB
  63. Code/Section 7/Code/sample.py 43KB
  64. Code/Section 5/Ch5_third_example.ipynb 27KB
  65. Code/Section 5/CH5_linear_regression_nn.ipynb 20KB
  66. Code/Section 5/data/mpg.csv 17KB
  67. Code/Section 6/CH6_CIFAR.ipynb 16KB
  68. Code/Section 4/Univariate_logistic_regression_keras.ipynb 14KB
  69. Code/Section 5/data/wine.csv 11KB
  70. Code/Section 8/stylize.py 9KB
  71. Code/Section 8/neural_style.py 9KB
  72. Code/Section 6/CH6_Mnist_final.py 5KB
  73. content.txt 4KB
  74. Code/Section 4/CH4_Univariate_logistic_regression.py 4KB
  75. Code/Section 1/iris.csv 4KB
  76. Code/Section 8/.ipynb_checkpoints/Cifar10-checkpoint.ipynb 3KB
  77. Code/Section 7/Code/train.py 2KB
  78. Code/Section 6/CH6_convolution.ipynb 2KB
  79. Code/Section 6/CH6_image_subsampling.ipynb 2KB
  80. Code/Section 3/utils.py 2KB
  81. Code/Section 8/vgg.py 2KB
  82. Code/Section 5/CH5_linear_regression_nn.py 2KB
  83. Code/Section 5/Ch5_third_example.py 2KB
  84. Code/Section 5/CH5_Nonlinear.py 2KB
  85. Code/Section 6/CH6_convolution.py 1KB
  86. Code/Section 6/CH6_image_subsampling.py 1KB
  87. Code/Section 4/Univariate_logistic_regression_keras.py 1KB
  88. Code/Section 1/csv_1.0.py 741B
  89. Code/Section 4/data/CHD.csv 609B
  90. Code/Section 6/data/cifar-10-batches-bin/readme.html 88B
  91. Code/Section 8/.ipynb_checkpoints/VGG retraining-checkpoint.ipynb 72B
  92. Code/Section 6/data/cifar-10-batches-bin/batches.meta.txt 61B