[FreeTutorials.Us] Udemy - machine-learning-course-with-python

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Files
  1. 02 Getting Started with Anaconda/attached_files/008 Navigating the Spyder Jupyter Notebook Interface/0204.zip 42.29KB
  2. 02 Getting Started with Anaconda/attached_files/009 Downloading the IRIS Datasets/0205.zip 228.57KB
  3. 02 Getting Started with Anaconda/attached_files/010 Data Exploration and Analysis/0206.zip 44.72KB
  4. 02 Getting Started with Anaconda/attached_files/011 Presenting Your Data/0207.zip 1.05MB
  5. 03 Regression/attached_files/014 Working with Scikit-Learn/0303.zip 911.87KB
  6. 03 Regression/attached_files/015 Boston Housing Data - EDA/0304.zip 1.89MB
  7. 03 Regression/attached_files/016 Correlation Analysis and Feature Selection/0305.zip 2.13MB
  8. 03 Regression/attached_files/017 Simple Linear Regression Modelling with Boston Housing Data/0306.zip 2.57MB
  9. 03 Regression/attached_files/018 Robust Regression/0307.zip 2.75MB
  10. 03 Regression/attached_files/019 Evaluate Model Performance/0308.zip 2.98MB
  11. 03 Regression/attached_files/020 Multiple Regression with statsmodel/0309.zip 2.62MB
  12. 03 Regression/attached_files/021 Multiple Regression and Feature Importance/0310.zip 2.70MB
  13. 03 Regression/attached_files/022 Ordinary Least Square Regression and Gradient Descent/0311.zip 141.36KB
  14. 03 Regression/attached_files/023 Regularised Method for Regression/0312.zip 258.65KB
  15. 03 Regression/attached_files/024 Polynomial Regression/0313.zip 374.85KB
  16. 03 Regression/attached_files/025 Dealing with Non-linear relationships/0314.zip 180.73KB
  17. 03 Regression/attached_files/026 Feature Importance Revisited/0315.zip 225.86KB
  18. 03 Regression/attached_files/027 Data Pre-Processing 1/0316.zip 155.83KB
  19. 03 Regression/attached_files/028 Data Pre-Processing 2/0317.zip 156.89KB
  20. 03 Regression/attached_files/029 Variance Bias Trade Off - Validation Curve/0318.zip 528.12KB
  21. 03 Regression/attached_files/030 Variance Bias Trade Off - Learning Curve/0319.zip 716.50KB
  22. 03 Regression/attached_files/031 Cross Validation/0320.zip 94.74KB
  23. 04 Classification/attached_files/033 Logistic Regression 1/0403.zip 19.42KB
  24. 04 Classification/attached_files/034 Logistic Regression 2/0404.zip 20.07KB
  25. 04 Classification/attached_files/035 MNIST Project 1 - Introduction/0405.zip 565.83KB
  26. 04 Classification/attached_files/036 MNIST Project 2 - SGDClassifier/0406.zip 565.83KB
  27. 04 Classification/attached_files/037 MNIST Project 3 - Performance Measures/0407.zip 566.17KB
  28. 04 Classification/attached_files/038 MNIST Project 4 - Confusion Matrix Precision Recall and F1 Score/0408.zip 573.92KB
  29. 04 Classification/attached_files/039 MNIST Project 5 - Precision and Recall Tradeoff/0409.zip 630.15KB
  30. 04 Classification/attached_files/040 MNIST Project 6 - The ROC Curve/0410.zip 684.19KB
  31. 05 Support Vector Machine SVM/attached_files/043 Support Vector Machine SVM Concepts/0502.zip 218.57KB
  32. 05 Support Vector Machine SVM/attached_files/044 Linear SVM Classification/0503.zip 446.64KB
  33. 05 Support Vector Machine SVM/attached_files/045 Polynomial Kernel/0504.zip 491.12KB
  34. 05 Support Vector Machine SVM/attached_files/046 Gaussian Radial Basis Function/0505.zip 533.45KB
  35. 05 Support Vector Machine SVM/attached_files/047 Support Vector Regression/0506.zip 573.08KB
  36. 06 Tree/attached_files/050 What is Decision Tree/0602.zip 113.33KB
  37. 06 Tree/attached_files/051 Training a Decision Tree/0603.zip 113.71KB
  38. 06 Tree/attached_files/052 Visualising a Decision Trees/0604.zip 158.70KB
  39. 06 Tree/attached_files/053 Decision Tree Learning Algorithm/0605.zip 229.29KB
  40. 06 Tree/attached_files/054 Decision Tree Regression/0606.zip 277.90KB
  41. 06 Tree/attached_files/055 Overfitting and Grid Search/0607.zip 297.92KB
  42. 06 Tree/attached_files/056 Where to From Here/0608.zip 309.73KB
  43. 06 Tree/attached_files/057 Project HR - Loading and preprocesing data/0609.zip 63.35KB
  44. 06 Tree/attached_files/058 Project HR - Modelling/0610.zip 64.03KB
  45. 07 Ensemble Machine Learning/attached_files/060 Ensemble Learning Methods Introduction/0702.zip 2.22KB
  46. 07 Ensemble Machine Learning/attached_files/061 Bagging Part 1/0703.zip 7.64KB
  47. 07 Ensemble Machine Learning/attached_files/062 Bagging Part 2/0704.zip 8.08KB
  48. 07 Ensemble Machine Learning/attached_files/063 Random Forests/0705.zip 8.74KB
  49. 07 Ensemble Machine Learning/attached_files/064 Extra-Trees/0706.zip 9.10KB
  50. 07 Ensemble Machine Learning/attached_files/065 AdaBoost/0707.zip 8.83KB
  51. 07 Ensemble Machine Learning/attached_files/066 Gradient Boosting Machine/0708.zip 60.46KB
  52. 07 Ensemble Machine Learning/attached_files/067 XGBoost/0709.zip 2.94KB
  53. 07 Ensemble Machine Learning/attached_files/068 Project HR - Human Resources Analytics/0710.zip 126.73KB
  54. 07 Ensemble Machine Learning/attached_files/069 Ensemble of ensembles Part 1/0711.zip 3.66KB
  55. 07 Ensemble Machine Learning/attached_files/070 Ensemble of ensembles Part 2/0712.zip 5.35KB
  56. 08 k-Nearest Neighbours kNN/attached_files/072 kNN Concepts/0802.zip 1.52KB
  57. 08 k-Nearest Neighbours kNN/attached_files/073 kNN and Iris Dataset Demo/0803.zip 26.18KB
  58. 08 k-Nearest Neighbours kNN/attached_files/075 Project Cancer Detection Part 1/0805.zip 40.76KB
  59. 08 k-Nearest Neighbours kNN/attached_files/076 Project Cancer Detection Part 2/0806.zip 40.76KB
  60. 09 Dimensionality Reduction/attached_files/078 Dimensionality Reduction Concept/0902.zip 2.05KB
  61. 09 Dimensionality Reduction/attached_files/079 PCA Introduction/0903.zip 87.32KB
  62. 09 Dimensionality Reduction/attached_files/082 Project Abalone/09-Project-Abalone.zip 16.21KB
  63. 09 Dimensionality Reduction/attached_files/083 Project Wine 2 Choosing the Number of Components/0906.zip 106.05KB
  64. 09 Dimensionality Reduction/attached_files/084 Kernel PCA/0907.zip 108.17KB
  65. 09 Dimensionality Reduction/attached_files/085 Kernel PCA Demo/0908.zip 108.17KB
  66. 09 Dimensionality Reduction/attached_files/086 LDA Comparison between LDA and PCA/0909.zip 77.12KB
  67. 10 Unsupervised Learning Clustering/attached_files/088 Clustering Concepts/1002.zip 439.67KB
  68. 10 Unsupervised Learning Clustering/attached_files/089 MLextend/1003.zip 439.67KB
  69. 10 Unsupervised Learning Clustering/attached_files/090 Wards Agglomerative Hierarchical Clustering/1004.zip 439.67KB
  70. 10 Unsupervised Learning Clustering/attached_files/091 Truncating Dendrogram/1005.zip 439.67KB
  71. 10 Unsupervised Learning Clustering/attached_files/092 k-Means Clustering/1006.zip 439.67KB
  72. 10 Unsupervised Learning Clustering/attached_files/093 Elbow Method/1007.zip 439.67KB
  73. 10 Unsupervised Learning Clustering/attached_files/094 Silhouette Analysis/1008.zip 439.67KB
  74. 10 Unsupervised Learning Clustering/attached_files/095 Mean Shift/1009.zip 439.67KB
  75. 02 Getting Started with Anaconda/quizzes/001 Getting Started.html 10.88KB
  76. 03 Regression/quizzes/002 Machine Learning Basic Concepts.html 8.95KB
  77. 03 Regression/quizzes/003 Section 3.html 11.42KB
  78. 01 Introduction/001 What Does the Course Cover.mp4 9.88MB
  79. 01 Introduction/002 How to Succeed in This Course.html 2.02KB
  80. 01 Introduction/003 Project Files.html 1.90KB
  81. 02 Getting Started with Anaconda/004 Windows OS Downloading Installing Anaconda.mp4 64.36MB
  82. 02 Getting Started with Anaconda/005 Windows OS Managing Environment.mp4 18.82MB
  83. 02 Getting Started with Anaconda/006 Mac OS Intructions on Installing Anaconda and Managing Environment.html 516B
  84. 02 Getting Started with Anaconda/007 Practice Activity Create a New Environment.html 737B
  85. 02 Getting Started with Anaconda/008 Navigating the Spyder Jupyter Notebook Interface.mp4 41.35MB
  86. 02 Getting Started with Anaconda/009 Downloading the IRIS Datasets.mp4 10.49MB
  87. 02 Getting Started with Anaconda/010 Data Exploration and Analysis.mp4 34.79MB
  88. 02 Getting Started with Anaconda/011 Presenting Your Data.mp4 46.52MB
  89. 03 Regression/012 Introduction.mp4 11.72MB
  90. 03 Regression/013 Categories of Machine Learning.mp4 22.36MB
  91. 03 Regression/014 Working with Scikit-Learn.mp4 45.94MB
  92. 03 Regression/015 Boston Housing Data - EDA.mp4 61.46MB
  93. 03 Regression/016 Correlation Analysis and Feature Selection.mp4 22.58MB
  94. 03 Regression/017 Simple Linear Regression Modelling with Boston Housing Data.mp4 33.80MB
  95. 03 Regression/018 Robust Regression.mp4 33.46MB
  96. 03 Regression/019 Evaluate Model Performance.mp4 59.14MB
  97. 03 Regression/020 Multiple Regression with statsmodel.mp4 59.64MB
  98. 03 Regression/021 Multiple Regression and Feature Importance.mp4 44.66MB
  99. 03 Regression/022 Ordinary Least Square Regression and Gradient Descent.mp4 50.03MB
  100. 03 Regression/023 Regularised Method for Regression.mp4 47.81MB
  101. 03 Regression/024 Polynomial Regression.mp4 43.81MB
  102. 03 Regression/025 Dealing with Non-linear relationships.mp4 28.44MB
  103. 03 Regression/026 Feature Importance Revisited.mp4 26.18MB
  104. 03 Regression/027 Data Pre-Processing 1.mp4 34.92MB
  105. 03 Regression/028 Data Pre-Processing 2.mp4 49.58MB
  106. 03 Regression/029 Variance Bias Trade Off - Validation Curve.mp4 43.83MB
  107. 03 Regression/030 Variance Bias Trade Off - Learning Curve.mp4 42.45MB
  108. 03 Regression/031 Cross Validation.mp4 44.68MB
  109. 04 Classification/032 Introduction.mp4 7.91MB
  110. 04 Classification/033 Logistic Regression 1.mp4 26.93MB
  111. 04 Classification/034 Logistic Regression 2.mp4 41.75MB
  112. 04 Classification/035 MNIST Project 1 - Introduction.mp4 34.55MB
  113. 04 Classification/036 MNIST Project 2 - SGDClassifier.mp4 25.47MB
  114. 04 Classification/037 MNIST Project 3 - Performance Measures.mp4 26.40MB
  115. 04 Classification/038 MNIST Project 4 - Confusion Matrix Precision Recall and F1 Score.mp4 46.08MB
  116. 04 Classification/039 MNIST Project 5 - Precision and Recall Tradeoff.mp4 43.91MB
  117. 04 Classification/040 MNIST Project 6 - The ROC Curve.mp4 33.78MB
  118. 04 Classification/041 MNIST Exercise.html 826B
  119. 05 Support Vector Machine SVM/042 Introduction.mp4 4.72MB
  120. 05 Support Vector Machine SVM/043 Support Vector Machine SVM Concepts.mp4 51.80MB
  121. 05 Support Vector Machine SVM/044 Linear SVM Classification.mp4 31.57MB
  122. 05 Support Vector Machine SVM/045 Polynomial Kernel.mp4 50.31MB
  123. 05 Support Vector Machine SVM/046 Gaussian Radial Basis Function.mp4 44.80MB
  124. 05 Support Vector Machine SVM/047 Support Vector Regression.mp4 17.39MB
  125. 05 Support Vector Machine SVM/048 Advantages and Disadvantages of SVM.mp4 13.11MB
  126. 06 Tree/049 Introduction.mp4 5.58MB
  127. 06 Tree/050 What is Decision Tree.mp4 34.07MB
  128. 06 Tree/051 Training a Decision Tree.mp4 16.59MB
  129. 06 Tree/052 Visualising a Decision Trees.mp4 55.25MB
  130. 06 Tree/053 Decision Tree Learning Algorithm.mp4 36.97MB
  131. 06 Tree/054 Decision Tree Regression.mp4 33.80MB
  132. 06 Tree/055 Overfitting and Grid Search.mp4 54.43MB
  133. 06 Tree/056 Where to From Here.mp4 11.62MB
  134. 06 Tree/057 Project HR - Loading and preprocesing data.mp4 56.76MB
  135. 06 Tree/058 Project HR - Modelling.mp4 16.50MB
  136. 07 Ensemble Machine Learning/059 Introduction.mp4 5.22MB
  137. 07 Ensemble Machine Learning/060 Ensemble Learning Methods Introduction.mp4 27.68MB
  138. 07 Ensemble Machine Learning/061 Bagging Part 1.mp4 55.47MB
  139. 07 Ensemble Machine Learning/062 Bagging Part 2.mp4 37.31MB
  140. 07 Ensemble Machine Learning/063 Random Forests.mp4 43.11MB
  141. 07 Ensemble Machine Learning/064 Extra-Trees.mp4 21.58MB
  142. 07 Ensemble Machine Learning/065 AdaBoost.mp4 39.82MB
  143. 07 Ensemble Machine Learning/066 Gradient Boosting Machine.mp4 44.87MB
  144. 07 Ensemble Machine Learning/067 XGBoost.mp4 51.35MB
  145. 07 Ensemble Machine Learning/068 Project HR - Human Resources Analytics.mp4 88.16MB
  146. 07 Ensemble Machine Learning/069 Ensemble of ensembles Part 1.mp4 52.03MB
  147. 07 Ensemble Machine Learning/070 Ensemble of ensembles Part 2.mp4 44.89MB
  148. 08 k-Nearest Neighbours kNN/071 kNN Introduction.mp4 4.37MB
  149. 08 k-Nearest Neighbours kNN/072 kNN Concepts.mp4 15.00MB
  150. 08 k-Nearest Neighbours kNN/073 kNN and Iris Dataset Demo.mp4 20.75MB
  151. 08 k-Nearest Neighbours kNN/074 Distance Metric.mp4 13.08MB
  152. 08 k-Nearest Neighbours kNN/075 Project Cancer Detection Part 1.mp4 49.40MB
  153. 08 k-Nearest Neighbours kNN/076 Project Cancer Detection Part 2.mp4 48.64MB
  154. 09 Dimensionality Reduction/077 Introduction.mp4 3.63MB
  155. 09 Dimensionality Reduction/078 Dimensionality Reduction Concept.mp4 25.73MB
  156. 09 Dimensionality Reduction/079 PCA Introduction.mp4 42.24MB
  157. 09 Dimensionality Reduction/080 Dimensionality Reduction Demo.mp4 14.64MB
  158. 09 Dimensionality Reduction/081 Project Wine 1 Dimensionality Reduction with PCA.mp4 46.11MB
  159. 09 Dimensionality Reduction/082 Project Abalone.html 458B
  160. 09 Dimensionality Reduction/083 Project Wine 2 Choosing the Number of Components.mp4 18.79MB
  161. 09 Dimensionality Reduction/084 Kernel PCA.mp4 35.84MB
  162. 09 Dimensionality Reduction/085 Kernel PCA Demo.mp4 16.01MB
  163. 09 Dimensionality Reduction/086 LDA Comparison between LDA and PCA.mp4 16.90MB
  164. 10 Unsupervised Learning Clustering/087 Introduction.mp4 4.03MB
  165. 10 Unsupervised Learning Clustering/088 Clustering Concepts.mp4 17.47MB
  166. 10 Unsupervised Learning Clustering/089 MLextend.mp4 22.58MB
  167. 10 Unsupervised Learning Clustering/090 Wards Agglomerative Hierarchical Clustering.mp4 44.12MB
  168. 10 Unsupervised Learning Clustering/091 Truncating Dendrogram.mp4 56.42MB
  169. 10 Unsupervised Learning Clustering/092 k-Means Clustering.mp4 36.59MB
  170. 10 Unsupervised Learning Clustering/093 Elbow Method.mp4 15.76MB
  171. 10 Unsupervised Learning Clustering/094 Silhouette Analysis.mp4 16.50MB
  172. 10 Unsupervised Learning Clustering/095 Mean Shift.mp4 25.68MB
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