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[DesireCourse.Net] Udemy - Practical Machine Learning by Example in Python

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视频 2021-10-6 23:48 2024-6-19 20:06 244 2.71 GB 101
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迅雷链接
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DesireCourse Net Udemy - Practical Machine Learning by Example in Python

文件列表
  1. 1. Course Structure and Development Environment/1. Course Structure and Development Environment.mp431.37MB
  2. 1. Course Structure and Development Environment/2. Course Quick Tips.mp432.08MB
  3. 1. Course Structure and Development Environment/3. Introduction to Jupyter Notebook.mp416.92MB
  4. 1. Course Structure and Development Environment/4. Jupyter notebook Text Cells.mp427.07MB
  5. 1. Course Structure and Development Environment/5. Jupyter notebook Code Cells.mp415.03MB
  6. 1. Course Structure and Development Environment/6. Jupyter notebook Math Markup and Magic Commands.mp423.35MB
  7. 1. Course Structure and Development Environment/8. Sharing Colab Notebooks.mp435.7MB
  8. 1. Course Structure and Development Environment/9. Artificial Intelligence, Machine Learning, and Deep Learning.mp425.15MB
  9. 10. Example Fraud detection/1. The problem.mp422.34MB
  10. 10. Example Fraud detection/11. Common questions.mp428.84MB
  11. 10. Example Fraud detection/2. Data analysis.mp441.75MB
  12. 10. Example Fraud detection/4. Unsupervised learning.mp428.85MB
  13. 10. Example Fraud detection/5. Data preparation.mp416.86MB
  14. 10. Example Fraud detection/6. Model definition.mp421.42MB
  15. 10. Example Fraud detection/7. Model training.mp425.11MB
  16. 10. Example Fraud detection/9. Making predictions.mp449.37MB
  17. 11. Next steps/1. Next steps.mp411.59MB
  18. 11. Next steps/2. Thank you.mp43.07MB
  19. 2. Python Quick Start/1. About this section.mp47.44MB
  20. 2. Python Quick Start/10. Dictionaries.mp432.06MB
  21. 2. Python Quick Start/11. Defining functions.mp434.67MB
  22. 2. Python Quick Start/12. Classes.mp462.46MB
  23. 2. Python Quick Start/13. File IO and Modules.mp433.75MB
  24. 2. Python Quick Start/15. Prompting for passwords.mp47.09MB
  25. 2. Python Quick Start/2. Basic Syntax.mp435.16MB
  26. 2. Python Quick Start/3. String formatting.mp452.36MB
  27. 2. Python Quick Start/4. Literal string interpolation.mp415.79MB
  28. 2. Python Quick Start/6. Type conversion.mp419.6MB
  29. 2. Python Quick Start/7. Flow control.mp423.5MB
  30. 2. Python Quick Start/8. Lists.mp422.36MB
  31. 3. Example Logistic Regression/1. The problem.mp427.97MB
  32. 3. Example Logistic Regression/10. Backpropagation.mp423.91MB
  33. 3. Example Logistic Regression/11. Model training.mp429.92MB
  34. 3. Example Logistic Regression/12. Making predictions.mp440.33MB
  35. 3. Example Logistic Regression/15. Test vs. train accuracy.mp418.97MB
  36. 3. Example Logistic Regression/16. Speeding up training.mp418.1MB
  37. 3. Example Logistic Regression/17. Improving the model.mp427.09MB
  38. 3. Example Logistic Regression/2. Machine Learning Development Process.mp414.03MB
  39. 3. Example Logistic Regression/3. Data analysis.mp458.98MB
  40. 3. Example Logistic Regression/5. The model.mp422.19MB
  41. 3. Example Logistic Regression/6. The forward function.mp437.85MB
  42. 3. Example Logistic Regression/7. Loss and cost functions.mp419.82MB
  43. 3. Example Logistic Regression/8. Gradient descent.mp446.27MB
  44. 4. Foundations NumPy/1. What is NumPy and why it is needed.mp48.12MB
  45. 4. Foundations NumPy/10. Visualizing data.mp433.72MB
  46. 4. Foundations NumPy/11. Images.mp431.8MB
  47. 4. Foundations NumPy/13. Reshaping data.mp411.15MB
  48. 4. Foundations NumPy/2. Creating data with NumPy.mp425MB
  49. 4. Foundations NumPy/3. Basic operations.mp414.7MB
  50. 4. Foundations NumPy/5. Introduction to Linear Regression.mp452.3MB
  51. 4. Foundations NumPy/6. Linear Regression Example.mp464.63MB
  52. 4. Foundations NumPy/8. More Complex Models.mp413.51MB
  53. 4. Foundations NumPy/9. Statistics and linear algebra.mp416.96MB
  54. 5. Foundations Tensorflow/1. About this section.mp418.09MB
  55. 5. Foundations Tensorflow/10. Prediction example.mp46.78MB
  56. 5. Foundations Tensorflow/11. Saving and restoring models.mp415.58MB
  57. 5. Foundations Tensorflow/12. The Three Body Problem.mp423.47MB
  58. 5. Foundations Tensorflow/2. Model example.mp428.95MB
  59. 5. Foundations Tensorflow/3. Model layers.mp413.2MB
  60. 5. Foundations Tensorflow/4. Activation functions.mp419.33MB
  61. 5. Foundations Tensorflow/5. Training example.mp423.54MB
  62. 5. Foundations Tensorflow/7. Loss functions.mp419.2MB
  63. 5. Foundations Tensorflow/8. Optimizers.mp416.4MB
  64. 6. Example Image recognition/1. The problem.mp419.42MB
  65. 6. Example Image recognition/10. Making predictions.mp412.29MB
  66. 6. Example Image recognition/11. Error analysis.mp415.42MB
  67. 6. Example Image recognition/13. Hyperparameter tuning.mp422.44MB
  68. 6. Example Image recognition/14. Hyperparameter tuning example.mp452.48MB
  69. 6. Example Image recognition/16. Common questions.mp427.85MB
  70. 6. Example Image recognition/2. Data analysis.mp438.32MB
  71. 6. Example Image recognition/4. Model selection.mp422.78MB
  72. 6. Example Image recognition/5. Data preparation.mp427MB
  73. 6. Example Image recognition/6. CNN Model Layers.mp422.97MB
  74. 6. Example Image recognition/7. Model definition.mp431.7MB
  75. 6. Example Image recognition/8. Model training.mp450.24MB
  76. 7. Foundations Pandas/1. What is Pandas and why is it useful.mp48.92MB
  77. 7. Foundations Pandas/2. Loading and inspecting data example.mp458.99MB
  78. 7. Foundations Pandas/3. Indexing and selecting data example.mp434.96MB
  79. 7. Foundations Pandas/5. Sorting and transforming data example.mp439.83MB
  80. 7. Foundations Pandas/6. Aggregations example.mp433.94MB
  81. 7. Foundations Pandas/7. Visualizing data.mp435.32MB
  82. 8. Example Recommendations/1. The problem.mp417.06MB
  83. 8. Example Recommendations/11. Predictions.mp45.7MB
  84. 8. Example Recommendations/12. Making predictions.mp429.53MB
  85. 8. Example Recommendations/13. Error analysis.mp418.61MB
  86. 8. Example Recommendations/15. Common questions.mp419.57MB
  87. 8. Example Recommendations/2. Data analysis.mp429.05MB
  88. 8. Example Recommendations/4. Model selection.mp426.96MB
  89. 8. Example Recommendations/5. Data preparation.mp436.17MB
  90. 8. Example Recommendations/7. Embedding layers.mp417.17MB
  91. 8. Example Recommendations/8. Model definition.mp442.25MB
  92. 8. Example Recommendations/9. Model training.mp429.34MB
  93. 9. Example Sentiment Analysis/1. The Problem.mp413.13MB
  94. 9. Example Sentiment Analysis/10. Transfer Learning with BERT.mp423.75MB
  95. 9. Example Sentiment Analysis/11. Transfer Learning Example.mp457.83MB
  96. 9. Example Sentiment Analysis/12. Fine Tuning and Prediction.mp439.54MB
  97. 9. Example Sentiment Analysis/2. Data Analysis.mp430.54MB
  98. 9. Example Sentiment Analysis/4. Supervised Learning.mp427.63MB
  99. 9. Example Sentiment Analysis/5. Data Preparation.mp444.37MB
  100. 9. Example Sentiment Analysis/7. Model Definition.mp429.01MB
  101. 9. Example Sentiment Analysis/8. Model Training.mp434.77MB
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