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[] Udemy - Machine Learning Regression Masterclass in Python

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  • 文件大小:5GB
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文件列表

  1. 4. REGRESSION KEY PERFORMANCE INDICATORS/4. Bias Variance Tradeoff.mp4 190MB
  2. 6. MULTIPLE LINEAR REGRESSION/5. Project #1 - Model Training and Evaluation.mp4 158MB
  3. 3. SIMPLE LINEAR REGRESSION/8. Project #1 - Test Model.mp4 144MB
  4. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/4. ML vs. DL vs. AI.mp4 144MB
  5. 9. LASSO AND RIDGE REGRESSION/5. Ridge and Lasso in Practice.mp4 142MB
  6. 6. MULTIPLE LINEAR REGRESSION/6. Project #1 - Model Results Evaluation.mp4 136MB
  7. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/12. Evaluate the Model.mp4 132MB
  8. 6. MULTIPLE LINEAR REGRESSION/12. Project #2 - Retraining Model.mp4 129MB
  9. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/9. Project - Visualize Dataset.mp4 129MB
  10. 4. REGRESSION KEY PERFORMANCE INDICATORS/2. Regression Metric Part 1.mp4 128MB
  11. 3. SIMPLE LINEAR REGRESSION/4. Project #1 - Overview.mp4 127MB
  12. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/11. Train the Model.mp4 122MB
  13. 6. MULTIPLE LINEAR REGRESSION/9. Project #2 - Data Visualization.mp4 118MB
  14. 3. SIMPLE LINEAR REGRESSION/2. Simple Linear Regression Intuition.mp4 98MB
  15. 7. LOGISTIC REGRESSION/7. Project #2 - Training Testing.mp4 93MB
  16. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/5. Theory Part 4.mp4 91MB
  17. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/14. Model Improvement with more features.mp4 91MB
  18. 9. LASSO AND RIDGE REGRESSION/2. Ridge Lasso Part 1.mp4 89MB
  19. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/8. Project - Load Dataset.mp4 87MB
  20. 7. LOGISTIC REGRESSION/8. Model Testing Visualization.mp4 86MB
  21. 5. POLYNOMIAL REGRESSION/5. Poly Regression - Linear Trainingtesting.mp4 79MB
  22. 6. MULTIPLE LINEAR REGRESSION/11. Project #2 - Model Evaluation.mp4 79MB
  23. 3. SIMPLE LINEAR REGRESSION/14. Project #2 - Model Testing.mp4 78MB
  24. 6. MULTIPLE LINEAR REGRESSION/4. Project #1 - Data Visualization.mp4 78MB
  25. 7. LOGISTIC REGRESSION/5. Project #2 - Visualization.mp4 77MB
  26. 4. REGRESSION KEY PERFORMANCE INDICATORS/3. Regression Metric Part 2.mp4 76MB
  27. 5. POLYNOMIAL REGRESSION/3. Poly Regression - Salary Load Data.mp4 74MB
  28. 3. SIMPLE LINEAR REGRESSION/6. Project #1 - Divide Data into Training and Testing.mp4 74MB
  29. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/13. Multiple Linear regression.mp4 72MB
  30. 3. SIMPLE LINEAR REGRESSION/5. Project #1 - Data Visualization.mp4 71MB
  31. 7. LOGISTIC REGRESSION/3. Confusion Matrix.mp4 71MB
  32. 6. MULTIPLE LINEAR REGRESSION/8. Project #2 - Load Data.mp4 70MB
  33. 9. LASSO AND RIDGE REGRESSION/3. Ridge Lasso Part 2.mp4 68MB
  34. 5. POLYNOMIAL REGRESSION/2. Polynomial Regression - Intuition.mp4 67MB
  35. 7. LOGISTIC REGRESSION/2. Logistic Regression Intuition.mp4 64MB
  36. 5. POLYNOMIAL REGRESSION/4. Poly Regression - Visualize Data.mp4 64MB
  37. 5. POLYNOMIAL REGRESSION/11. Poly Regression - Economies Poly.mp4 63MB
  38. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/1. Course Welcome Message.mp4 61MB
  39. 3. SIMPLE LINEAR REGRESSION/3. Least Squares.mp4 60MB
  40. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/10. Scale the Data.mp4 59MB
  41. 6. MULTIPLE LINEAR REGRESSION/3. Project #1 - Load Data and Libraries.mp4 57MB
  42. 5. POLYNOMIAL REGRESSION/10. Poly Regression - Economies Linear -2.mp4 56MB
  43. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/4. Theory Part 3.mp4 56MB
  44. 5. POLYNOMIAL REGRESSION/6. Poly Regression - Poly Part 1.mp4 55MB
  45. 6. MULTIPLE LINEAR REGRESSION/10. Project #2 - Train the Model.mp4 53MB
  46. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/3. Course Overview.mp4 53MB
  47. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/6. Theory Part 5.mp4 50MB
  48. 3. SIMPLE LINEAR REGRESSION/7. Project #1 - Train Model.mp4 50MB
  49. 5. POLYNOMIAL REGRESSION/9. Poly Regression - Economies Linear -1.mp4 49MB
  50. 3. SIMPLE LINEAR REGRESSION/11. Project #2 - Visualization.mp4 48MB
  51. 2. ANACONDA AND JUPYTER INSTALLATION/1. Download and Set up Anaconda.mp4 45MB
  52. 7. LOGISTIC REGRESSION/6. Project #2 - Data Cleaning.mp4 44MB
  53. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/2. Theory Part 1.mp4 40MB
  54. 7. LOGISTIC REGRESSION/4. Project #2 - Data Import.mp4 37MB
  55. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/7. Theory Part 6.mp4 36MB
  56. 5. POLYNOMIAL REGRESSION/7. Poly Regression - Poly Part 2.mp4 36MB
  57. 3. SIMPLE LINEAR REGRESSION/10. Project #2 - Solution.mp4 34MB
  58. 9. LASSO AND RIDGE REGRESSION/4. Ridge Lasso Part 3.mp4 33MB
  59. 5. POLYNOMIAL REGRESSION/8. Poly Regression Project 2 Overview.mp4 32MB
  60. 2. ANACONDA AND JUPYTER INSTALLATION/2. What is Jupiter Notebook.mp4 32MB
  61. 3. SIMPLE LINEAR REGRESSION/12. Project #2 - Prepare Training and Testing Data.mp4 32MB
  62. 3. SIMPLE LINEAR REGRESSION/13. Project #2 - Test Model.mp4 32MB
  63. 7. LOGISTIC REGRESSION/1. Logistic Regression Intro.mp4 30MB
  64. 3. SIMPLE LINEAR REGRESSION/9. Project #2 - Overview.mp4 30MB
  65. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/3. Theory Part 2.mp4 28MB
  66. 3. SIMPLE LINEAR REGRESSION/1. Intro to Simple Linear Regression.mp4 27MB
  67. 6. MULTIPLE LINEAR REGRESSION/7. Project #2 - Overview.mp4 26MB
  68. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/3.1 ML Regression Course Package.zip.zip 25MB
  69. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/2. Updates on Udemy Reviews.mp4 23MB
  70. 9. LASSO AND RIDGE REGRESSION/1. Ridge and Lasso Intro.mp4 23MB
  71. 6. MULTIPLE LINEAR REGRESSION/2. Multiple Linear Regression Overview.mp4 21MB
  72. 6. MULTIPLE LINEAR REGRESSION/1. Multiple Linear Regression Intro.mp4 20MB
  73. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/1. Artificial Neural Networks Intro.mp4 16MB
  74. 5. POLYNOMIAL REGRESSION/1. Polynomial Regression Intro.mp4 15MB
  75. 4. REGRESSION KEY PERFORMANCE INDICATORS/1. Regression Metrics Intro.mp4 13MB
  76. 4. REGRESSION KEY PERFORMANCE INDICATORS/4. Bias Variance Tradeoff.vtt 29KB
  77. 6. MULTIPLE LINEAR REGRESSION/5. Project #1 - Model Training and Evaluation.vtt 25KB
  78. 3. SIMPLE LINEAR REGRESSION/8. Project #1 - Test Model.vtt 24KB
  79. 3. SIMPLE LINEAR REGRESSION/4. Project #1 - Overview.vtt 24KB
  80. 4. REGRESSION KEY PERFORMANCE INDICATORS/2. Regression Metric Part 1.vtt 21KB
  81. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/4. ML vs. DL vs. AI.vtt 21KB
  82. 6. MULTIPLE LINEAR REGRESSION/6. Project #1 - Model Results Evaluation.vtt 21KB
  83. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/12. Evaluate the Model.vtt 20KB
  84. 9. LASSO AND RIDGE REGRESSION/5. Ridge and Lasso in Practice.vtt 18KB
  85. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/11. Train the Model.vtt 18KB
  86. 6. MULTIPLE LINEAR REGRESSION/12. Project #2 - Retraining Model.vtt 17KB
  87. 6. MULTIPLE LINEAR REGRESSION/9. Project #2 - Data Visualization.vtt 16KB
  88. 3. SIMPLE LINEAR REGRESSION/2. Simple Linear Regression Intuition.vtt 16KB
  89. 7. LOGISTIC REGRESSION/3. Confusion Matrix.vtt 16KB
  90. 7. LOGISTIC REGRESSION/7. Project #2 - Training Testing.vtt 16KB
  91. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/9. Project - Visualize Dataset.vtt 16KB
  92. 3. SIMPLE LINEAR REGRESSION/5. Project #1 - Data Visualization.vtt 14KB
  93. 3. SIMPLE LINEAR REGRESSION/6. Project #1 - Divide Data into Training and Testing.vtt 14KB
  94. 5. POLYNOMIAL REGRESSION/5. Poly Regression - Linear Trainingtesting.vtt 14KB
  95. 7. LOGISTIC REGRESSION/5. Project #2 - Visualization.vtt 14KB
  96. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/5. Theory Part 4.vtt 13KB
  97. 3. SIMPLE LINEAR REGRESSION/14. Project #2 - Model Testing.vtt 13KB
  98. 5. POLYNOMIAL REGRESSION/3. Poly Regression - Salary Load Data.vtt 13KB
  99. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/8. Project - Load Dataset.vtt 13KB
  100. 5. POLYNOMIAL REGRESSION/2. Polynomial Regression - Intuition.vtt 13KB
  101. 7. LOGISTIC REGRESSION/8. Model Testing Visualization.vtt 13KB
  102. 6. MULTIPLE LINEAR REGRESSION/4. Project #1 - Data Visualization.vtt 13KB
  103. 9. LASSO AND RIDGE REGRESSION/2. Ridge Lasso Part 1.vtt 12KB
  104. 6. MULTIPLE LINEAR REGRESSION/11. Project #2 - Model Evaluation.vtt 12KB
  105. 4. REGRESSION KEY PERFORMANCE INDICATORS/3. Regression Metric Part 2.vtt 12KB
  106. 5. POLYNOMIAL REGRESSION/4. Poly Regression - Visualize Data.vtt 12KB
  107. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/3. Course Overview.vtt 12KB
  108. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/14. Model Improvement with more features.vtt 12KB
  109. 7. LOGISTIC REGRESSION/2. Logistic Regression Intuition.vtt 11KB
  110. 5. POLYNOMIAL REGRESSION/11. Poly Regression - Economies Poly.vtt 10KB
  111. 9. LASSO AND RIDGE REGRESSION/3. Ridge Lasso Part 2.vtt 10KB
  112. 3. SIMPLE LINEAR REGRESSION/7. Project #1 - Train Model.vtt 10KB
  113. 6. MULTIPLE LINEAR REGRESSION/8. Project #2 - Load Data.vtt 10KB
  114. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/13. Multiple Linear regression.vtt 10KB
  115. 6. MULTIPLE LINEAR REGRESSION/10. Project #2 - Train the Model.vtt 10KB
  116. 5. POLYNOMIAL REGRESSION/10. Poly Regression - Economies Linear -2.vtt 10KB
  117. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/4. Theory Part 3.vtt 10KB
  118. 3. SIMPLE LINEAR REGRESSION/3. Least Squares.vtt 9KB
  119. 5. POLYNOMIAL REGRESSION/6. Poly Regression - Poly Part 1.vtt 9KB
  120. 6. MULTIPLE LINEAR REGRESSION/3. Project #1 - Load Data and Libraries.vtt 9KB
  121. 3. SIMPLE LINEAR REGRESSION/11. Project #2 - Visualization.vtt 9KB
  122. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/6. Theory Part 5.vtt 9KB
  123. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/10. Scale the Data.vtt 9KB
  124. 5. POLYNOMIAL REGRESSION/9. Poly Regression - Economies Linear -1.vtt 8KB
  125. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/2. Theory Part 1.vtt 7KB
  126. 7. LOGISTIC REGRESSION/6. Project #2 - Data Cleaning.vtt 7KB
  127. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/7. Theory Part 6.vtt 7KB
  128. 5. POLYNOMIAL REGRESSION/7. Poly Regression - Poly Part 2.vtt 6KB
  129. 7. LOGISTIC REGRESSION/4. Project #2 - Data Import.vtt 6KB
  130. 3. SIMPLE LINEAR REGRESSION/12. Project #2 - Prepare Training and Testing Data.vtt 6KB
  131. 3. SIMPLE LINEAR REGRESSION/13. Project #2 - Test Model.vtt 6KB
  132. 2. ANACONDA AND JUPYTER INSTALLATION/1. Download and Set up Anaconda.vtt 6KB
  133. 3. SIMPLE LINEAR REGRESSION/10. Project #2 - Solution.vtt 5KB
  134. 9. LASSO AND RIDGE REGRESSION/4. Ridge Lasso Part 3.vtt 5KB
  135. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/3. Theory Part 2.vtt 5KB
  136. 5. POLYNOMIAL REGRESSION/8. Poly Regression Project 2 Overview.vtt 5KB
  137. 2. ANACONDA AND JUPYTER INSTALLATION/2. What is Jupiter Notebook.vtt 5KB
  138. 3. SIMPLE LINEAR REGRESSION/9. Project #2 - Overview.vtt 4KB
  139. 6. MULTIPLE LINEAR REGRESSION/7. Project #2 - Overview.vtt 4KB
  140. 6. MULTIPLE LINEAR REGRESSION/2. Multiple Linear Regression Overview.vtt 4KB
  141. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/1. Course Welcome Message.vtt 3KB
  142. 7. LOGISTIC REGRESSION/1. Logistic Regression Intro.vtt 2KB
  143. 3. SIMPLE LINEAR REGRESSION/1. Intro to Simple Linear Regression.vtt 2KB
  144. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/2. Updates on Udemy Reviews.vtt 1KB
  145. 6. MULTIPLE LINEAR REGRESSION/1. Multiple Linear Regression Intro.vtt 1KB
  146. 9. LASSO AND RIDGE REGRESSION/1. Ridge and Lasso Intro.vtt 1KB
  147. 10. Bonus Lectures/1. YOUR SPECIAL BONUS.html 1KB
  148. 8. APPLY ARTIFICIAL NEURAL NETWORKS TO PERFROM REGRESSION TASKS/1. Artificial Neural Networks Intro.vtt 962B
  149. 5. POLYNOMIAL REGRESSION/1. Polynomial Regression Intro.vtt 922B
  150. 4. REGRESSION KEY PERFORMANCE INDICATORS/1. Regression Metrics Intro.vtt 815B
  151. Readme.txt 140B
  152. 1. INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/[Tutorialsplanet.NET].url 128B
  153. 10. Bonus Lectures/[Tutorialsplanet.NET].url 128B
  154. 5. POLYNOMIAL REGRESSION/[Tutorialsplanet.NET].url 128B
  155. 7. LOGISTIC REGRESSION/[Tutorialsplanet.NET].url 128B
  156. [Tutorialsplanet.NET].url 128B