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[DesireCourse.Net] Udemy - Machine Learning with Javascript

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视频 2023-1-26 07:43 2024-5-22 23:39 84 10.1 GB 183
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DesireCourse Net Udemy - Machine Learning with Javascript

文件列表
  1. 01 What is Machine Learning/001 Getting Started - How to Get Help.mp48.35MB
  2. 01 What is Machine Learning/002 Solving Machine Learning Problems.mp462.77MB
  3. 01 What is Machine Learning/003 A Complete Walkthrough.mp4109.13MB
  4. 01 What is Machine Learning/004 App Setup.mp419.27MB
  5. 01 What is Machine Learning/005 Problem Outline.mp431.21MB
  6. 01 What is Machine Learning/006 Identifying Relevant Data.mp433.91MB
  7. 01 What is Machine Learning/007 Dataset Structures.mp448.24MB
  8. 01 What is Machine Learning/008 Recording Observation Data.mp432.74MB
  9. 01 What is Machine Learning/009 What Type of Problem.mp447.03MB
  10. 02 Algorithm Overview/010 How K-Nearest Neighbor Works.mp493.32MB
  11. 02 Algorithm Overview/011 Lodash Review.mp464.93MB
  12. 02 Algorithm Overview/012 Implementing KNN.mp459.34MB
  13. 02 Algorithm Overview/013 Finishing KNN Implementation.mp450.28MB
  14. 02 Algorithm Overview/014 Testing the Algorithm.mp444.96MB
  15. 02 Algorithm Overview/015 Interpreting Bad Results.mp440.75MB
  16. 02 Algorithm Overview/016 Test and Training Data.mp445.2MB
  17. 02 Algorithm Overview/017 Randomizing Test Data.mp436MB
  18. 02 Algorithm Overview/018 Generalizing KNN.mp438.99MB
  19. 02 Algorithm Overview/019 Gauging Accuracy.mp454.01MB
  20. 02 Algorithm Overview/020 Printing a Report.mp433.29MB
  21. 02 Algorithm Overview/021 Refactoring Accuracy Reporting.mp452.3MB
  22. 02 Algorithm Overview/022 Investigating Optimal K Values.mp4129.13MB
  23. 02 Algorithm Overview/023 Updating KNN for Multiple Features.mp470.61MB
  24. 02 Algorithm Overview/024 Multi-Dimensional KNN.mp444.2MB
  25. 02 Algorithm Overview/025 N-Dimension Distance.mp478.87MB
  26. 02 Algorithm Overview/026 Arbitrary Feature Spaces.mp471.25MB
  27. 02 Algorithm Overview/027 Magnitude Offsets in Features.mp464.06MB
  28. 02 Algorithm Overview/028 Feature Normalization.mp472.91MB
  29. 02 Algorithm Overview/029 Normalization with MinMax.mp467.04MB
  30. 02 Algorithm Overview/030 Applying Normalization.mp445.35MB
  31. 02 Algorithm Overview/031 Feature Selection with KNN.mp480.36MB
  32. 02 Algorithm Overview/032 Objective Feature Picking.mp465.97MB
  33. 02 Algorithm Overview/033 Evaluating Different Feature Values.mp427.97MB
  34. 03 Onwards to Tensorflow JS/034 Lets Get Our Bearings.mp476.61MB
  35. 03 Onwards to Tensorflow JS/035 A Plan to Move Forward.mp448.65MB
  36. 03 Onwards to Tensorflow JS/036 Tensor Shape and Dimension.mp4114.28MB
  37. 03 Onwards to Tensorflow JS/037 Elementwise Operations.mp458.36MB
  38. 03 Onwards to Tensorflow JS/038 Broadcasting Operations.mp462.05MB
  39. 03 Onwards to Tensorflow JS/039 Logging Tensor Data.mp426MB
  40. 03 Onwards to Tensorflow JS/040 Tensor Accessors.mp430.46MB
  41. 03 Onwards to Tensorflow JS/041 Creating Slices of Data.mp458.91MB
  42. 03 Onwards to Tensorflow JS/042 Tensor Concatenation.mp444.13MB
  43. 03 Onwards to Tensorflow JS/043 Summing Values Along an Axis.mp441.36MB
  44. 03 Onwards to Tensorflow JS/044 Massaging Dimensions with ExpandDims.mp457.01MB
  45. 04 Applications of Tensorflow/045 KNN with Regression.mp454.98MB
  46. 04 Applications of Tensorflow/046 A Change in Data Structure.mp441.34MB
  47. 04 Applications of Tensorflow/047 KNN with Tensorflow.mp478.71MB
  48. 04 Applications of Tensorflow/048 Maintaining Order Relationships.mp457.75MB
  49. 04 Applications of Tensorflow/049 Sorting Tensors.mp462.84MB
  50. 04 Applications of Tensorflow/050 Averaging Top Values.mp458.13MB
  51. 04 Applications of Tensorflow/051 Moving to the Editor.mp434.33MB
  52. 04 Applications of Tensorflow/052 Loading CSV Data.mp489.32MB
  53. 04 Applications of Tensorflow/053 Running an Analysis.mp452.5MB
  54. 04 Applications of Tensorflow/054 Reporting Error Percentages.mp464.49MB
  55. 04 Applications of Tensorflow/055 Normalization or Standardization.mp492.97MB
  56. 04 Applications of Tensorflow/056 Numerical Standardization with Tensorflow.mp453.05MB
  57. 04 Applications of Tensorflow/057 Applying Standardization.mp441.46MB
  58. 04 Applications of Tensorflow/058 Debugging Calculations.mp486.71MB
  59. 04 Applications of Tensorflow/059 What Now.mp442.32MB
  60. 05 Getting Started with Gradient Descent/060 Linear Regression.mp425.38MB
  61. 05 Getting Started with Gradient Descent/061 Why Linear Regression.mp450.34MB
  62. 05 Getting Started with Gradient Descent/062 Understanding Gradient Descent.mp4126.76MB
  63. 05 Getting Started with Gradient Descent/063 Guessing Coefficients with MSE.mp493.46MB
  64. 05 Getting Started with Gradient Descent/064 Observations Around MSE.mp456.11MB
  65. 05 Getting Started with Gradient Descent/065 Derivatives.mp477.95MB
  66. 05 Getting Started with Gradient Descent/066 Gradient Descent in Action.mp4115.35MB
  67. 05 Getting Started with Gradient Descent/067 Quick Breather and Review.mp465.79MB
  68. 05 Getting Started with Gradient Descent/068 Why a Learning Rate.mp4187.28MB
  69. 05 Getting Started with Gradient Descent/069 Answering Common Questions.mp440.94MB
  70. 05 Getting Started with Gradient Descent/070 Gradient Descent with Multiple Terms.mp444.19MB
  71. 05 Getting Started with Gradient Descent/071 Multiple Terms in Action.mp4123.15MB
  72. 06 Gradient Descent with Tensorflow/072 Project Overview.mp457.04MB
  73. 06 Gradient Descent with Tensorflow/073 Data Loading.mp443.48MB
  74. 06 Gradient Descent with Tensorflow/074 Default Algorithm Options.mp462.66MB
  75. 06 Gradient Descent with Tensorflow/075 Formulating the Training Loop.mp427.67MB
  76. 06 Gradient Descent with Tensorflow/076 Initial Gradient Descent Implementation.mp487.92MB
  77. 06 Gradient Descent with Tensorflow/077 Calculating MSE Slopes.mp467.13MB
  78. 06 Gradient Descent with Tensorflow/078 Updating Coefficients.mp433.86MB
  79. 06 Gradient Descent with Tensorflow/079 Interpreting Results.mp4101.71MB
  80. 06 Gradient Descent with Tensorflow/080 Matrix Multiplication.mp467.46MB
  81. 06 Gradient Descent with Tensorflow/081 More on Matrix Multiplication.mp463.24MB
  82. 06 Gradient Descent with Tensorflow/082 Matrix Form of Slope Equations.mp459.6MB
  83. 06 Gradient Descent with Tensorflow/083 Simplification with Matrix Multiplication.mp490.79MB
  84. 06 Gradient Descent with Tensorflow/084 How it All Works Together.mp4143.82MB
  85. 07 Increasing Performance with Vectorized Solutions/085 Refactoring the Linear Regression Class.mp472.71MB
  86. 07 Increasing Performance with Vectorized Solutions/086 Refactoring to One Equation.mp484.8MB
  87. 07 Increasing Performance with Vectorized Solutions/087 A Few More Changes.mp466.16MB
  88. 07 Increasing Performance with Vectorized Solutions/088 Same Results Or Not.mp433.83MB
  89. 07 Increasing Performance with Vectorized Solutions/089 Calculating Model Accuracy.mp480.36MB
  90. 07 Increasing Performance with Vectorized Solutions/090 Implementing Coefficient of Determination.mp475.78MB
  91. 07 Increasing Performance with Vectorized Solutions/091 Dealing with Bad Accuracy.mp471.41MB
  92. 07 Increasing Performance with Vectorized Solutions/092 Reminder on Standardization.mp444.49MB
  93. 07 Increasing Performance with Vectorized Solutions/093 Data Processing in a Helper Method.mp437.17MB
  94. 07 Increasing Performance with Vectorized Solutions/094 Reapplying Standardization.mp457.96MB
  95. 07 Increasing Performance with Vectorized Solutions/095 Fixing Standardization Issues.mp447.84MB
  96. 07 Increasing Performance with Vectorized Solutions/096 Massaging Learning Rates.mp436.44MB
  97. 07 Increasing Performance with Vectorized Solutions/097 Moving Towards Multivariate Regression.mp4121.42MB
  98. 07 Increasing Performance with Vectorized Solutions/098 Refactoring for Multivariate Analysis.mp482.35MB
  99. 07 Increasing Performance with Vectorized Solutions/099 Learning Rate Optimization.mp476.69MB
  100. 07 Increasing Performance with Vectorized Solutions/100 Recording MSE History.mp451.94MB
  101. 07 Increasing Performance with Vectorized Solutions/101 Updating Learning Rate.mp462.14MB
  102. 08 Plotting Data with Javascript/102 Observing Changing Learning Rate and MSE.mp445.83MB
  103. 08 Plotting Data with Javascript/103 Plotting MSE Values.mp461.39MB
  104. 08 Plotting Data with Javascript/104 Plotting MSE History against B Values.mp447.8MB
  105. 09 Gradient Descent Alterations/105 Batch and Stochastic Gradient Descent.mp477.23MB
  106. 09 Gradient Descent Alterations/106 Refactoring Towards Batch Gradient Descent.mp455.11MB
  107. 09 Gradient Descent Alterations/107 Determining Batch Size and Quantity.mp466.08MB
  108. 09 Gradient Descent Alterations/108 Iterating Over Batches.mp467.45MB
  109. 09 Gradient Descent Alterations/109 Evaluating Batch Gradient Descent Results.mp466.23MB
  110. 09 Gradient Descent Alterations/110 Making Predictions with the Model.mp479.49MB
  111. 10 Natural Binary Classification/111 Introducing Logistic Regression.mp423.44MB
  112. 10 Natural Binary Classification/112 Logistic Regression in Action.mp461.07MB
  113. 10 Natural Binary Classification/113 Bad Equation Fits.mp455.39MB
  114. 10 Natural Binary Classification/114 The Sigmoid Equation.mp445.44MB
  115. 10 Natural Binary Classification/115 Decision Boundaries.mp479.18MB
  116. 10 Natural Binary Classification/116 Changes for Logistic Regression.mp412.49MB
  117. 10 Natural Binary Classification/117 Project Setup for Logistic Regression.mp459.4MB
  118. 10 Natural Binary Classification/119 Importing Vehicle Data.mp438.95MB
  119. 10 Natural Binary Classification/120 Encoding Label Values.mp448.58MB
  120. 10 Natural Binary Classification/121 Updating Linear Regression for Logistic Regression.mp470.29MB
  121. 10 Natural Binary Classification/122 The Sigmoid Equation with Logistic Regression.mp432.77MB
  122. 10 Natural Binary Classification/123 A Touch More Refactoring.mp487.42MB
  123. 10 Natural Binary Classification/124 Gauging Classification Accuracy.mp436.7MB
  124. 10 Natural Binary Classification/125 Implementing a Test Function.mp454.71MB
  125. 10 Natural Binary Classification/126 Variable Decision Boundaries.mp468.31MB
  126. 10 Natural Binary Classification/127 Mean Squared Error vs Cross Entropy.mp460.2MB
  127. 10 Natural Binary Classification/128 Refactoring with Cross Entropy.mp449.45MB
  128. 10 Natural Binary Classification/129 Finishing the Cost Refactor.mp449.09MB
  129. 10 Natural Binary Classification/130 Plotting Changing Cost History.mp442.95MB
  130. 11 Multi-Value Classification/131 Multinominal Logistic Regression.mp425MB
  131. 11 Multi-Value Classification/132 A Smart Refactor to Multinominal Analysis.mp449.97MB
  132. 11 Multi-Value Classification/133 A Smarter Refactor.mp438.29MB
  133. 11 Multi-Value Classification/134 A Single Instance Approach.mp4103.55MB
  134. 11 Multi-Value Classification/135 Refactoring to Multi-Column Weights.mp448.49MB
  135. 11 Multi-Value Classification/136 A Problem to Test Multinominal Classification.mp448.45MB
  136. 11 Multi-Value Classification/137 Classifying Continuous Values.mp444.55MB
  137. 11 Multi-Value Classification/138 Training a Multinominal Model.mp466.08MB
  138. 11 Multi-Value Classification/139 Marginal vs Conditional Probability.mp495.18MB
  139. 11 Multi-Value Classification/140 Sigmoid vs Softmax.mp462.75MB
  140. 11 Multi-Value Classification/141 Refactoring Sigmoid to Softmax.mp448.87MB
  141. 11 Multi-Value Classification/142 Implementing Accuracy Gauges.mp428.71MB
  142. 11 Multi-Value Classification/143 Calculating Accuracy.mp431.3MB
  143. 12 Image Recognition In Action/144 Handwriting Recognition.mp424.69MB
  144. 12 Image Recognition In Action/145 Greyscale Values.mp455.34MB
  145. 12 Image Recognition In Action/146 Many Features.mp444.76MB
  146. 12 Image Recognition In Action/147 Flattening Image Data.mp457.76MB
  147. 12 Image Recognition In Action/148 Encoding Label Values.mp462MB
  148. 12 Image Recognition In Action/149 Implementing an Accuracy Gauge.mp479.94MB
  149. 12 Image Recognition In Action/150 Unchanging Accuracy.mp420.3MB
  150. 12 Image Recognition In Action/151 Debugging the Calculation Process.mp489.04MB
  151. 12 Image Recognition In Action/152 Dealing with Zero Variances.mp447.9MB
  152. 12 Image Recognition In Action/153 Backfilling Variance.mp425.72MB
  153. 13 Performance Optimization/154 Handing Large Datasets.mp444.46MB
  154. 13 Performance Optimization/155 Minimizing Memory Usage.mp438.18MB
  155. 13 Performance Optimization/156 Creating Memory Snapshots.mp449.05MB
  156. 13 Performance Optimization/157 The Javascript Garbage Collector.mp455.8MB
  157. 13 Performance Optimization/158 Shallow vs Retained Memory Usage.mp456.89MB
  158. 13 Performance Optimization/159 Measuring Memory Usage.mp496.63MB
  159. 13 Performance Optimization/160 Releasing References.mp435.98MB
  160. 13 Performance Optimization/161 Measuring Footprint Reduction.mp443.3MB
  161. 13 Performance Optimization/162 Optimization Tensorflow Memory Usage.mp418.53MB
  162. 13 Performance Optimization/163 Tensorflows Eager Memory Usage.mp446.81MB
  163. 13 Performance Optimization/164 Cleaning up Tensors with Tidy.mp424.26MB
  164. 13 Performance Optimization/165 Implementing TF Tidy.mp437.59MB
  165. 13 Performance Optimization/166 Tidying the Training Loop.mp445.99MB
  166. 13 Performance Optimization/167 Measuring Reduced Memory Usage.mp418.11MB
  167. 13 Performance Optimization/168 One More Optimization.mp427.49MB
  168. 13 Performance Optimization/169 Final Memory Report.mp436.24MB
  169. 13 Performance Optimization/170 Plotting Cost History.mp447.59MB
  170. 13 Performance Optimization/171 NaN in Cost History.mp446.37MB
  171. 13 Performance Optimization/172 Fixing Cost History.mp446.77MB
  172. 13 Performance Optimization/173 Massaging Learning Parameters.mp422.55MB
  173. 13 Performance Optimization/174 Improving Model Accuracy.mp455.01MB
  174. 14 Appendix Custom CSV Loader/175 Loading CSV Files.mp415.85MB
  175. 14 Appendix Custom CSV Loader/176 A Test Dataset.mp49.58MB
  176. 14 Appendix Custom CSV Loader/177 Reading Files from Disk.mp418.59MB
  177. 14 Appendix Custom CSV Loader/178 Splitting into Columns.mp420.34MB
  178. 14 Appendix Custom CSV Loader/179 Dropping Trailing Columns.mp418.4MB
  179. 14 Appendix Custom CSV Loader/180 Parsing Number Values.mp431.36MB
  180. 14 Appendix Custom CSV Loader/181 Custom Value Parsing.mp436.72MB
  181. 14 Appendix Custom CSV Loader/182 Extracting Data Columns.mp457.27MB
  182. 14 Appendix Custom CSV Loader/183 Shuffling Data via Seed Phrase.mp452.14MB
  183. 14 Appendix Custom CSV Loader/184 Splitting Test and Training.mp475.65MB
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