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[] Udemy - Machine Learning & Data Science A-Z Hands-on Python 2021

  • 收录时间:2021-08-09 16:03:15
  • 文件大小:7GB
  • 下载次数:1
  • 最近下载:2021-08-09 16:03:15
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文件列表

  1. 06 Supervised Learning - Regression/008 Random Forest Model Development.mp4 246MB
  2. 05 Supervised Learning - Classification/001 Supervised Learning Models - Introduction and Understanding the Data.mp4 234MB
  3. 05 Supervised Learning - Classification/004 k-NN Training-Set and Test-Set Creation.mp4 228MB
  4. 03 Data Preprocessing/006 Missing Values2.mp4 219MB
  5. 06 Supervised Learning - Regression/006 Polynomial Linear Regression Model Development.mp4 219MB
  6. 06 Supervised Learning - Regression/001 Simple and Multiple Linear Regression Concepts.mp4 212MB
  7. 03 Data Preprocessing/003 Statistics2.mp4 207MB
  8. 02 Machine Learning Useful Packages (Libraries)/013 Visualization with Matplotlib2.mp4 205MB
  9. 02 Machine Learning Useful Packages (Libraries)/011 Pandas4.mp4 203MB
  10. 02 Machine Learning Useful Packages (Libraries)/014 Visualization with Matplotlib3.mp4 189MB
  11. 03 Data Preprocessing/012 Normalization.mp4 187MB
  12. 05 Supervised Learning - Classification/013 Model Evaluation - Calculating with Python.mp4 174MB
  13. 06 Supervised Learning - Regression/004 Evaluation Metrics - Implementation.mp4 160MB
  14. 03 Data Preprocessing/001 Reading and Modifying a Dataset.mp4 155MB
  15. 02 Machine Learning Useful Packages (Libraries)/006 NumPy5.mp4 153MB
  16. 07 Unsupervised Learning - Clustering Techniques/010 Hierarchical Clustering Model Development.mp4 146MB
  17. 02 Machine Learning Useful Packages (Libraries)/015 Visualization with Matplotlib4.mp4 143MB
  18. 05 Supervised Learning - Classification/003 k-NN Model Development.mp4 141MB
  19. 02 Machine Learning Useful Packages (Libraries)/007 NumPy6.mp4 134MB
  20. 08 Hyper Parameter Optimization (Model Tuning)/004 k-NN - Model Tuning.mp4 134MB
  21. 03 Data Preprocessing/008 Outlier Detection2.mp4 131MB
  22. 03 Data Preprocessing/005 Missing Values1.mp4 130MB
  23. 02 Machine Learning Useful Packages (Libraries)/016 Visualization with Matplotlib5.mp4 129MB
  24. 08 Hyper Parameter Optimization (Model Tuning)/002 Support Vector Regression - Model Tuning.mp4 126MB
  25. 06 Supervised Learning - Regression/010 Support Vector Regression Model Development.mp4 121MB
  26. 02 Machine Learning Useful Packages (Libraries)/010 Pandas3.mp4 118MB
  27. 02 Machine Learning Useful Packages (Libraries)/009 Pandas2.mp4 117MB
  28. 05 Supervised Learning - Classification/011 Logistic Regression Model Development.mp4 112MB
  29. 03 Data Preprocessing/004 Statistics3 - Covariance.mp4 107MB
  30. 07 Unsupervised Learning - Clustering Techniques/005 K-means Model Development2.mp4 104MB
  31. 07 Unsupervised Learning - Clustering Techniques/006 K-means - Model Evaluation.mp4 102MB
  32. 02 Machine Learning Useful Packages (Libraries)/012 Visualization with Matplotlib1.mp4 99MB
  33. 02 Machine Learning Useful Packages (Libraries)/008 Pandas1.mp4 96MB
  34. 07 Unsupervised Learning - Clustering Techniques/008 DBSCAN Model Development.mp4 87MB
  35. 02 Machine Learning Useful Packages (Libraries)/004 NumPy3.mp4 85MB
  36. 05 Supervised Learning - Classification/012 Model Evaluation Concepts.mp4 83MB
  37. 06 Supervised Learning - Regression/002 Multiple Linear Regression - Model Development.mp4 76MB
  38. 03 Data Preprocessing/007 Outlier Detection1.mp4 73MB
  39. 08 Hyper Parameter Optimization (Model Tuning)/005 Overfitting and Underfitting.mp4 72MB
  40. 01 Introduction/006 Installation of Required Libraries.mp4 71MB
  41. 05 Supervised Learning - Classification/006 Decision Tree Model Development.mp4 67MB
  42. 03 Data Preprocessing/010 Concatenation.mp4 66MB
  43. 05 Supervised Learning - Classification/008 Naive Bayes Concepts.mp4 59MB
  44. 05 Supervised Learning - Classification/009 Naive Bayes Model Development.mp4 59MB
  45. 03 Data Preprocessing/011 Dummy Variable.mp4 58MB
  46. 02 Machine Learning Useful Packages (Libraries)/003 NumPy2.mp4 57MB
  47. 02 Machine Learning Useful Packages (Libraries)/005 NumPy4.mp4 57MB
  48. 05 Supervised Learning - Classification/007 Decision Tree - Cross Validation.mp4 55MB
  49. 06 Supervised Learning - Regression/003 Evaluation Metrics - Concepts.mp4 49MB
  50. 05 Supervised Learning - Classification/002 k-NN Concepts.mp4 48MB
  51. 01 Introduction/007 Spyder Interface.mp4 46MB
  52. 04 Machine Learning Introduction/001 Learning Types.mp4 45MB
  53. 07 Unsupervised Learning - Clustering Techniques/002 K-means Concepts1.mp4 45MB
  54. 07 Unsupervised Learning - Clustering Techniques/001 Introduction.mp4 38MB
  55. 02 Machine Learning Useful Packages (Libraries)/002 NumPy1.mp4 37MB
  56. 07 Unsupervised Learning - Clustering Techniques/004 K-means Model Development1.mp4 36MB
  57. 03 Data Preprocessing/002 Statistics1.mp4 34MB
  58. 03 Data Preprocessing/009 Outlier Detection3.mp4 31MB
  59. 06 Supervised Learning - Regression/007 Random Forest Concepts.mp4 30MB
  60. 06 Supervised Learning - Regression/009 Support Vector Regression Concepts.mp4 27MB
  61. 07 Unsupervised Learning - Clustering Techniques/007 DBSCAN Concepts.mp4 27MB
  62. 06 Supervised Learning - Regression/005 Polynomial Linear Regression Concepts.mp4 26MB
  63. 01 Introduction/002 What is Machine Learning_ Some Basic Terms.mp4 26MB
  64. 05 Supervised Learning - Classification/005 Decision Tree Concepts.mp4 26MB
  65. 07 Unsupervised Learning - Clustering Techniques/009 Hierarchical Clustering Concepts.mp4 24MB
  66. 01 Introduction/005 IDE Installation.mp4 22MB
  67. 07 Unsupervised Learning - Clustering Techniques/003 K-means Concepts2.mp4 21MB
  68. 01 Introduction/001 Course Content.mp4 17MB
  69. 08 Hyper Parameter Optimization (Model Tuning)/001 Introduction.mp4 17MB
  70. 08 Hyper Parameter Optimization (Model Tuning)/003 K-Means - Model Tuning.mp4 15MB
  71. 05 Supervised Learning - Classification/010 Logistic Regression Concepts.mp4 11MB
  72. 01 Introduction/004 Python IDE.mp4 8MB
  73. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter6.Regression.py 4KB
  74. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter5.Classification.py 3KB
  75. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter2.Matplotlib.py 3KB
  76. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter3.Preprocessing.py 3KB
  77. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter8.Parameter Tuning.py 2KB
  78. 01 Introduction/003 Python Installation.html 1KB
  79. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter7.Clustering.py 1KB
  80. 02 Machine Learning Useful Packages (Libraries)/001 Python Source Codes.html 1KB
  81. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter2.Pandas.py 1KB
  82. 02 Machine Learning Useful Packages (Libraries)/008 Python Source Codes/Chapter2.NumPy.py 1KB
  83. 02 Machine Learning Useful Packages (Libraries)/018 Data_Set.txt 580B
  84. 03 Data Preprocessing/024 Data_Set.txt 580B
  85. 03 Data Preprocessing/033 Data_New.txt 201B
  86. 0. Websites you may like/[FCS Forum].url 133B
  87. 0. Websites you may like/[FreeCourseSite.com].url 127B
  88. 0. Websites you may like/[CourseClub.ME].url 122B
  89. 02 Machine Learning Useful Packages (Libraries)/Readme.txt 70B
  90. 03 Data Preprocessing/Readme.txt 70B
  91. 0. Websites you may like/[GigaCourse.Com].url 49B