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Title [FreeCourseSite.com] Udemy - Machine Learning with Javascript
Category
Size 10.74GB

Files List
Please note that this page does not hosts or makes available any of the listed filenames. You cannot download any of those files from here.
[CourseClub.NET].url 123B
[FCS Forum].url 133B
[FreeCourseSite.com].url 127B
1. Batch and Stochastic Gradient Descent.mp4 77.24MB
1. Batch and Stochastic Gradient Descent.vtt 10.11KB
1. Getting Started - How to Get Help.mp4 8.36MB
1. Getting Started - How to Get Help.vtt 1.55KB
1. Handing Large Datasets.mp4 44.47MB
1. Handing Large Datasets.vtt 6.17KB
1. Handwriting Recognition.mp4 24.70MB
1. Handwriting Recognition.vtt 3.15KB
1. How K-Nearest Neighbor Works.mp4 93.33MB
1. How K-Nearest Neighbor Works.vtt 11.46KB
1. Introducing Logistic Regression.mp4 23.45MB
1. Introducing Logistic Regression.vtt 3.45KB
1. KNN with Regression.mp4 54.99MB
1. KNN with Regression.vtt 7.06KB
1. Let's Get Our Bearings.mp4 76.62MB
1. Let's Get Our Bearings.vtt 10.83KB
1. Linear Regression.mp4 25.39MB
1. Linear Regression.vtt 25.39MB
1. Loading CSV Files.mp4 15.86MB
1. Loading CSV Files.vtt 2.98KB
1. Multinominal Logistic Regression.mp4 25.00MB
1. Multinominal Logistic Regression.vtt 3.16KB
1. Observing Changing Learning Rate and MSE.mp4 45.84MB
1. Observing Changing Learning Rate and MSE.vtt 5.93KB
1. Project Overview.mp4 57.04MB
1. Project Overview.vtt 46.14MB
1. Refactoring the Linear Regression Class.mp4 72.72MB
1. Refactoring the Linear Regression Class.vtt 10.23KB
10. Answering Common Questions.mp4 40.95MB
10. Answering Common Questions.vtt 5.25KB
10. Backfilling Variance.mp4 25.73MB
10. Backfilling Variance.vtt 25.73MB
10. Creating Slices of Data.mp4 58.92MB
10. Creating Slices of Data.vtt 10.17KB
10. Encoding Label Values.mp4 48.59MB
10. Encoding Label Values.vtt 6.03KB
10. Gauging Accuracy.mp4 54.02MB
10. Gauging Accuracy.vtt 7.00KB
10. More on Matrix Multiplication.mp4 63.25MB
10. More on Matrix Multiplication.vtt 8.24KB
10. Reapplying Standardization.mp4 57.96MB
10. Reapplying Standardization.vtt 7.52KB
10. Reporting Error Percentages.mp4 64.50MB
10. Reporting Error Percentages.vtt 8.22KB
10. Sigmoid vs Softmax.mp4 62.76MB
10. Sigmoid vs Softmax.vtt 8.64KB
10. Splitting Test and Training.mp4 75.66MB
10. Splitting Test and Training.vtt 10.45KB
10. Tensorflow's Eager Memory Usage.mp4 46.81MB
10. Tensorflow's Eager Memory Usage.vtt 6.14KB
11. Cleaning up Tensors with Tidy.mp4 24.27MB
11. Cleaning up Tensors with Tidy.vtt 3.86KB
11. Fixing Standardization Issues.mp4 47.85MB
11. Fixing Standardization Issues.vtt 7.86KB
11. Gradient Descent with Multiple Terms.mp4 44.20MB
11. Gradient Descent with Multiple Terms.vtt 6.57KB
11. Matrix Form of Slope Equations.mp4 59.60MB
11. Matrix Form of Slope Equations.vtt 8.49KB
11. Normalization or Standardization.mp4 92.97MB
11. Normalization or Standardization.vtt 10.30KB
11. Printing a Report.mp4 33.30MB
11. Printing a Report.vtt 4.40KB
11. Refactoring Sigmoid to Softmax.mp4 48.88MB
11. Refactoring Sigmoid to Softmax.vtt 6.50KB
11. Tensor Concatenation.mp4 44.14MB
11. Tensor Concatenation.vtt 7.45KB
11. Updating Linear Regression for Logistic Regression.mp4 70.29MB
11. Updating Linear Regression for Logistic Regression.vtt 9.80KB
12. Implementing Accuracy Gauges.mp4 28.72MB
12. Implementing Accuracy Gauges.vtt 3.76KB
12. Implementing TF Tidy.mp4 37.60MB
12. Implementing TF Tidy.vtt 4.77KB
12. Massaging Learning Rates.mp4 36.44MB
12. Massaging Learning Rates.vtt 4.16KB
12. Multiple Terms in Action.mp4 123.16MB
12. Multiple Terms in Action.vtt 123.17MB
12. Numerical Standardization with Tensorflow.mp4 53.06MB
12. Numerical Standardization with Tensorflow.vtt 10.34KB
12. Refactoring Accuracy Reporting.mp4 52.31MB
12. Refactoring Accuracy Reporting.vtt 6.71KB
12. Simplification with Matrix Multiplication.mp4 90.80MB
12. Simplification with Matrix Multiplication.vtt 12.59KB
12. Summing Values Along an Axis.mp4 41.37MB
12. Summing Values Along an Axis.vtt 7.27KB
12. The Sigmoid Equation with Logistic Regression.mp4 32.78MB
12. The Sigmoid Equation with Logistic Regression.vtt 5.99KB
13. Applying Standardization.mp4 41.47MB
13. Applying Standardization.vtt 41.47MB
13. A Touch More Refactoring.mp4 87.43MB
13. A Touch More Refactoring.vtt 10.38KB
13. Calculating Accuracy.mp4 31.31MB
13. Calculating Accuracy.vtt 4.46KB
13. How it All Works Together!.mp4 143.82MB
13. How it All Works Together!.vtt 18.25KB
13. Investigating Optimal K Values.mp4 129.14MB
13. Investigating Optimal K Values.vtt 15.72KB
13. Massaging Dimensions with ExpandDims.mp4 57.02MB
13. Massaging Dimensions with ExpandDims.vtt 10.78KB
13. Moving Towards Multivariate Regression.mp4 121.42MB
13. Moving Towards Multivariate Regression.vtt 15.95KB
13. Tidying the Training Loop.mp4 45.99MB
13. Tidying the Training Loop.vtt 5.48KB
14. Debugging Calculations.mp4 86.72MB
14. Debugging Calculations.vtt 11.46KB
14. Gauging Classification Accuracy.mp4 36.71MB
14. Gauging Classification Accuracy.vtt 4.81KB
14. Measuring Reduced Memory Usage.mp4 18.12MB
14. Measuring Reduced Memory Usage.vtt 2.19KB
14. Refactoring for Multivariate Analysis.mp4 82.36MB
14. Refactoring for Multivariate Analysis.vtt 10.49KB
14. Updating KNN for Multiple Features.mp4 70.62MB
14. Updating KNN for Multiple Features.vtt 9.05KB
15. Implementing a Test Function.mp4 54.71MB
15. Implementing a Test Function.vtt 7.46KB
15. Learning Rate Optimization.mp4 76.69MB
15. Learning Rate Optimization.vtt 11.06KB
15. Multi-Dimensional KNN.mp4 44.21MB
15. Multi-Dimensional KNN.vtt 44.22MB
15. One More Optimization.mp4 27.50MB
15. One More Optimization.vtt 27.50MB
15. What Now.mp4 42.33MB
15. What Now.vtt 5.68KB
16. Final Memory Report.mp4 36.25MB
16. Final Memory Report.vtt 3.93KB
16. N-Dimension Distance.mp4 78.88MB
16. N-Dimension Distance.vtt 13.39KB
16. Recording MSE History.mp4 51.95MB
16. Recording MSE History.vtt 7.11KB
16. Variable Decision Boundaries.mp4 68.32MB
16. Variable Decision Boundaries.vtt 10.06KB
17. Arbitrary Feature Spaces.mp4 71.26MB
17. Arbitrary Feature Spaces.vtt 11.73KB
17. Mean Squared Error vs Cross Entropy.mp4 60.20MB
17. Mean Squared Error vs Cross Entropy.vtt 7.86KB
17. Plotting Cost History.mp4 47.60MB
17. Plotting Cost History.vtt 5.77KB
17. Updating Learning Rate.mp4 62.15MB
17. Updating Learning Rate.vtt 8.86KB
18. Magnitude Offsets in Features.mp4 64.06MB
18. Magnitude Offsets in Features.vtt 7.61KB
18. NaN in Cost History.mp4 46.37MB
18. NaN in Cost History.vtt 6.02KB
18. Refactoring with Cross Entropy.mp4 49.46MB
18. Refactoring with Cross Entropy.vtt 7.18KB
19. Feature Normalization.mp4 72.92MB
19. Feature Normalization.vtt 10.15KB
19. Finishing the Cost Refactor.mp4 49.10MB
19. Finishing the Cost Refactor.vtt 5.96KB
19. Fixing Cost History.mp4 46.78MB
19. Fixing Cost History.vtt 6.30KB
2. A Change in Data Structure.mp4 41.35MB
2. A Change in Data Structure.vtt 41.36MB
2. A Plan to Move Forward.mp4 48.66MB
2. A Plan to Move Forward.vtt 6.85KB
2. A Smart Refactor to Multinominal Analysis.mp4 49.97MB
2. A Smart Refactor to Multinominal Analysis.vtt 7.26KB
2. A Test Dataset.mp4 9.59MB
2. A Test Dataset.vtt 2.55KB
2. Data Loading.mp4 43.49MB
2. Data Loading.vtt 6.83KB
2. Greyscale Values.mp4 55.35MB
2. Greyscale Values.vtt 7.02KB
2. Lodash Review.mp4 64.94MB
2. Lodash Review.vtt 64.94MB
2. Logistic Regression in Action.mp4 61.07MB
2. Logistic Regression in Action.vtt 9.49KB
2. Minimizing Memory Usage.mp4 38.19MB
2. Minimizing Memory Usage.vtt 6.60KB
2. Plotting MSE Values.mp4 61.40MB
2. Plotting MSE Values.vtt 7.23KB
2. Refactoring to One Equation.mp4 84.81MB
2. Refactoring to One Equation.vtt 12.16KB
2. Refactoring Towards Batch Gradient Descent.mp4 55.11MB
2. Refactoring Towards Batch Gradient Descent.vtt 7.09KB
2. Solving Machine Learning Problems.mp4 62.78MB
2. Solving Machine Learning Problems.vtt 8.19KB
2. Why Linear Regression.mp4 50.35MB
2. Why Linear Regression.vtt 6.76KB
20. Massaging Learning Parameters.mp4 22.56MB
20. Massaging Learning Parameters.vtt 2.44KB
20. Normalization with MinMax.mp4 67.05MB
20. Normalization with MinMax.vtt 9.10KB
20. Plotting Changing Cost History.mp4 42.95MB
20. Plotting Changing Cost History.vtt 4.95KB
21. Applying Normalization.mp4 45.36MB
21. Applying Normalization.vtt 6.04KB
21. Improving Model Accuracy.mp4 55.02MB
21. Improving Model Accuracy.vtt 5.93KB
22. Feature Selection with KNN.mp4 80.37MB
22. Feature Selection with KNN.vtt 11.20KB
23. Objective Feature Picking.mp4 65.98MB
23. Objective Feature Picking.vtt 8.23KB
24. Evaluating Different Feature Values.mp4 27.97MB
24. Evaluating Different Feature Values.vtt 3.71KB
3. A Complete Walkthrough.mp4 109.14MB
3. A Complete Walkthrough.vtt 13.34KB
3. A Few More Changes.mp4 66.16MB
3. A Few More Changes.vtt 8.86KB
3. A Smarter Refactor!.mp4 38.30MB
3. A Smarter Refactor!.vtt 5.24KB
3. Bad Equation Fits.mp4 55.39MB
3. Bad Equation Fits.vtt 7.62KB
3. Creating Memory Snapshots.mp4 49.06MB
3. Creating Memory Snapshots.vtt 7.16KB
3. Default Algorithm Options.mp4 62.66MB
3. Default Algorithm Options.vtt 11.23KB
3. Determining Batch Size and Quantity.mp4 66.09MB
3. Determining Batch Size and Quantity.vtt 7.84KB
3. Implementing KNN.mp4 59.34MB
3. Implementing KNN.vtt 9.26KB
3. KNN with Tensorflow.mp4 78.72MB
3. KNN with Tensorflow.vtt 12.97KB
3. Many Features.mp4 44.77MB
3. Many Features.vtt 4.74KB
3. Plotting MSE History against B Values.mp4 47.81MB
3. Plotting MSE History against B Values.vtt 6.22KB
3. Reading Files from Disk.mp4 18.60MB
3. Reading Files from Disk.vtt 3.91KB
3. Tensor Shape and Dimension.mp4 114.29MB
3. Tensor Shape and Dimension.vtt 16.68KB
3. Understanding Gradient Descent.mp4 126.77MB
3. Understanding Gradient Descent.vtt 17.00KB
4. App Setup.mp4 19.27MB
4. App Setup.vtt 3.03KB
4. A Single Instance Approach.mp4 103.56MB
4. A Single Instance Approach.vtt 103.57MB
4. Finishing KNN Implementation.mp4 50.28MB
4. Finishing KNN Implementation.vtt 7.72KB
4. Flattening Image Data.mp4 57.77MB
4. Flattening Image Data.vtt 7.80KB
4. Formulating the Training Loop.mp4 27.68MB
4. Formulating the Training Loop.vtt 4.44KB
4. Guessing Coefficients with MSE.mp4 93.47MB
4. Guessing Coefficients with MSE.vtt 13.57KB
4. Iterating Over Batches.mp4 67.46MB
4. Iterating Over Batches.vtt 10.56KB
4. Maintaining Order Relationships.mp4 57.76MB
4. Maintaining Order Relationships.vtt 9.30KB
4. Same Results Or Not.mp4 33.84MB
4. Same Results Or Not.vtt 4.80KB
4. Splitting into Columns.mp4 20.35MB
4. Splitting into Columns.vtt 3.74KB
4. Tensor Dimension and Shapes.html 139B
4. The Javascript Garbage Collector.mp4 55.81MB
4. The Javascript Garbage Collector.vtt 8.95KB
4. The Sigmoid Equation.mp4 45.45MB
4. The Sigmoid Equation.vtt 6.42KB
5. Calculating Model Accuracy.mp4 80.37MB
5. Calculating Model Accuracy.vtt 11.67KB
5. Decision Boundaries.mp4 79.18MB
5. Decision Boundaries.vtt 10.56KB
5. Dropping Trailing Columns.mp4 18.41MB
5. Dropping Trailing Columns.vtt 3.42KB
5. Elementwise Operations.mp4 58.36MB
5. Elementwise Operations.vtt 10.45KB
5. Encoding Label Values.mp4 62.01MB
5. Encoding Label Values.vtt 7.42KB
5. Evaluating Batch Gradient Descent Results.mp4 66.24MB
5. Evaluating Batch Gradient Descent Results.vtt 7.98KB
5. Initial Gradient Descent Implementation.mp4 87.93MB
5. Initial Gradient Descent Implementation.vtt 12.48KB
5. Observations Around MSE.mp4 56.11MB
5. Observations Around MSE.vtt 8.19KB
5. Problem Outline.mp4 31.22MB
5. Problem Outline.vtt 4.31KB
5. Refactoring to Multi-Column Weights.mp4 48.50MB
5. Refactoring to Multi-Column Weights.vtt 6.69KB
5. Shallow vs Retained Memory Usage.mp4 56.90MB
5. Shallow vs Retained Memory Usage.vtt 8.05KB
5. Sorting Tensors.mp4 62.85MB
5. Sorting Tensors.vtt 10.64KB
5. Testing the Algorithm.mp4 44.97MB
5. Testing the Algorithm.vtt 6.24KB
6. A Problem to Test Multinominal Classification.mp4 48.46MB
6. A Problem to Test Multinominal Classification.vtt 6.33KB
6. Averaging Top Values.mp4 58.13MB
6. Averaging Top Values.vtt 10.28KB
6. Broadcasting Operations.mp4 62.06MB
6. Broadcasting Operations.vtt 9.35KB
6. Calculating MSE Slopes.mp4 67.14MB
6. Calculating MSE Slopes.vtt 8.46KB
6. Changes for Logistic Regression.mp4 12.50MB
6. Changes for Logistic Regression.vtt 1.76KB
6. Derivatives!.mp4 77.96MB
6. Derivatives!.vtt 77.96MB
6. Identifying Relevant Data.mp4 33.91MB
6. Identifying Relevant Data.vtt 5.88KB
6. Implementing an Accuracy Gauge.mp4 79.95MB
6. Implementing an Accuracy Gauge.vtt 10.01KB
6. Implementing Coefficient of Determination.mp4 75.79MB
6. Implementing Coefficient of Determination.vtt 10.33KB
6. Interpreting Bad Results.mp4 40.76MB
6. Interpreting Bad Results.vtt 5.78KB
6. Making Predictions with the Model.mp4 79.49MB
6. Making Predictions with the Model.vtt 10.48KB
6. Measuring Memory Usage.mp4 96.64MB
6. Measuring Memory Usage.vtt 12.01KB
6. Parsing Number Values.mp4 31.37MB
6. Parsing Number Values.vtt 4.79KB
7. Broadcasting Elementwise Operations.html 139B
7. Classifying Continuous Values.mp4 44.56MB
7. Classifying Continuous Values.vtt 6.18KB
7. Custom Value Parsing.mp4 36.72MB
7. Custom Value Parsing.vtt 5.75KB
7. Dataset Structures.mp4 48.25MB
7. Dataset Structures.vtt 8.12KB
7. Dealing with Bad Accuracy.mp4 71.42MB
7. Dealing with Bad Accuracy.vtt 10.41KB
7. Gradient Descent in Action.mp4 115.36MB
7. Gradient Descent in Action.vtt 16.07KB
7. Moving to the Editor.mp4 34.33MB
7. Moving to the Editor.vtt 4.66KB
7. Project Setup for Logistic Regression.mp4 59.41MB
7. Project Setup for Logistic Regression.vtt 8.14KB
7. Releasing References.mp4 35.98MB
7. Releasing References.vtt 4.36KB
7. Test and Training Data.mp4 45.21MB
7. Test and Training Data.vtt 5.38KB
7. Unchanging Accuracy.mp4 20.30MB
7. Unchanging Accuracy.vtt 2.89KB
7. Updating Coefficients.mp4 33.86MB
7. Updating Coefficients.vtt 33.88MB
8.1 regressions.zip.zip 34.30KB
8. Debugging the Calculation Process.mp4 89.05MB
8. Debugging the Calculation Process.vtt 11.31KB
8. Extracting Data Columns.mp4 57.28MB
8. Extracting Data Columns.vtt 6.83KB
8. Interpreting Results.mp4 101.71MB
8. Interpreting Results.vtt 13.60KB
8. Loading CSV Data.mp4 89.33MB
8. Loading CSV Data.vtt 13.19KB
8. Logging Tensor Data.mp4 26.00MB
8. Logging Tensor Data.vtt 5.50KB
8. Measuring Footprint Reduction.mp4 43.31MB
8. Measuring Footprint Reduction.vtt 5.46KB
8. Project Download.html 215B
8. Quick Breather and Review.mp4 65.80MB
8. Quick Breather and Review.vtt 8.05KB
8. Randomizing Test Data.mp4 36.01MB
8. Randomizing Test Data.vtt 5.01KB
8. Recording Observation Data.mp4 32.74MB
8. Recording Observation Data.vtt 5.34KB
8. Reminder on Standardization.mp4 44.50MB
8. Reminder on Standardization.vtt 6.15KB
8. Training a Multinominal Model.mp4 66.09MB
8. Training a Multinominal Model.vtt 8.62KB
9. Data Processing in a Helper Method.mp4 37.18MB
9. Data Processing in a Helper Method.vtt 4.91KB
9. Dealing with Zero Variances.mp4 47.91MB
9. Dealing with Zero Variances.vtt 8.78KB
9. Generalizing KNN.mp4 39.00MB
9. Generalizing KNN.vtt 4.98KB
9. Importing Vehicle Data.mp4 38.96MB
9. Importing Vehicle Data.vtt 5.85KB
9. Marginal vs Conditional Probability.mp4 95.19MB
9. Marginal vs Conditional Probability.vtt 14.02KB
9. Matrix Multiplication.mp4 67.47MB
9. Matrix Multiplication.vtt 9.91KB
9. Optimization Tensorflow Memory Usage.mp4 18.54MB
9. Optimization Tensorflow Memory Usage.vtt 2.35KB
9. Running an Analysis.mp4 52.50MB
9. Running an Analysis.vtt 8.16KB
9. Shuffling Data via Seed Phrase.mp4 52.14MB
9. Shuffling Data via Seed Phrase.vtt 7.42KB
9. Tensor Accessors.mp4 30.46MB
9. Tensor Accessors.vtt 7.48KB
9. What Type of Problem.mp4 47.04MB
9. What Type of Problem.vtt 6.74KB
9. Why a Learning Rate.mp4 187.28MB
9. Why a Learning Rate.vtt 22.69KB
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Israel (IL) 1
India (IN) 1
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