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[FreeCourseLab.com] Udemy - Machine Learning with Javascript
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2019-6-10 19:52
2024-9-6 22:32
129
10.1 GB
183
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FreeCourseLab
com
Udemy
-
Machine
Learning
with
Javascript
文件列表
1. What is Machine Learning/1. Getting Started - How to Get Help.mp4
8.35MB
1. What is Machine Learning/2. Solving Machine Learning Problems.mp4
62.77MB
1. What is Machine Learning/3. A Complete Walkthrough.mp4
109.13MB
1. What is Machine Learning/4. App Setup.mp4
19.27MB
1. What is Machine Learning/5. Problem Outline.mp4
31.21MB
1. What is Machine Learning/6. Identifying Relevant Data.mp4
33.91MB
1. What is Machine Learning/7. Dataset Structures.mp4
48.25MB
1. What is Machine Learning/8. Recording Observation Data.mp4
32.74MB
1. What is Machine Learning/9. What Type of Problem.mp4
47.03MB
10. Natural Binary Classification/1. Introducing Logistic Regression.mp4
23.45MB
10. Natural Binary Classification/10. Encoding Label Values.mp4
48.58MB
10. Natural Binary Classification/11. Updating Linear Regression for Logistic Regression.mp4
70.3MB
10. Natural Binary Classification/12. The Sigmoid Equation with Logistic Regression.mp4
32.78MB
10. Natural Binary Classification/13. A Touch More Refactoring.mp4
87.42MB
10. Natural Binary Classification/14. Gauging Classification Accuracy.mp4
36.7MB
10. Natural Binary Classification/15. Implementing a Test Function.mp4
54.71MB
10. Natural Binary Classification/16. Variable Decision Boundaries.mp4
68.32MB
10. Natural Binary Classification/17. Mean Squared Error vs Cross Entropy.mp4
60.2MB
10. Natural Binary Classification/18. Refactoring with Cross Entropy.mp4
49.45MB
10. Natural Binary Classification/19. Finishing the Cost Refactor.mp4
49.09MB
10. Natural Binary Classification/2. Logistic Regression in Action.mp4
61.07MB
10. Natural Binary Classification/20. Plotting Changing Cost History.mp4
42.95MB
10. Natural Binary Classification/3. Bad Equation Fits.mp4
55.4MB
10. Natural Binary Classification/4. The Sigmoid Equation.mp4
45.44MB
10. Natural Binary Classification/5. Decision Boundaries.mp4
79.18MB
10. Natural Binary Classification/6. Changes for Logistic Regression.mp4
12.49MB
10. Natural Binary Classification/7. Project Setup for Logistic Regression.mp4
59.4MB
10. Natural Binary Classification/9. Importing Vehicle Data.mp4
38.95MB
11. Multi-Value Classification/1. Multinominal Logistic Regression.mp4
25MB
11. Multi-Value Classification/10. Sigmoid vs Softmax.mp4
62.75MB
11. Multi-Value Classification/11. Refactoring Sigmoid to Softmax.mp4
48.87MB
11. Multi-Value Classification/12. Implementing Accuracy Gauges.mp4
28.71MB
11. Multi-Value Classification/13. Calculating Accuracy.mp4
31.3MB
11. Multi-Value Classification/2. A Smart Refactor to Multinominal Analysis.mp4
49.97MB
11. Multi-Value Classification/3. A Smarter Refactor!.mp4
38.29MB
11. Multi-Value Classification/4. A Single Instance Approach.mp4
103.56MB
11. Multi-Value Classification/5. Refactoring to Multi-Column Weights.mp4
48.49MB
11. Multi-Value Classification/6. A Problem to Test Multinominal Classification.mp4
48.45MB
11. Multi-Value Classification/7. Classifying Continuous Values.mp4
44.55MB
11. Multi-Value Classification/8. Training a Multinominal Model.mp4
66.09MB
11. Multi-Value Classification/9. Marginal vs Conditional Probability.mp4
95.18MB
12. Image Recognition In Action/1. Handwriting Recognition.mp4
24.69MB
12. Image Recognition In Action/10. Backfilling Variance.mp4
25.72MB
12. Image Recognition In Action/2. Greyscale Values.mp4
55.35MB
12. Image Recognition In Action/3. Many Features.mp4
44.76MB
12. Image Recognition In Action/4. Flattening Image Data.mp4
57.76MB
12. Image Recognition In Action/5. Encoding Label Values.mp4
62MB
12. Image Recognition In Action/6. Implementing an Accuracy Gauge.mp4
79.94MB
12. Image Recognition In Action/7. Unchanging Accuracy.mp4
20.3MB
12. Image Recognition In Action/8. Debugging the Calculation Process.mp4
89.05MB
12. Image Recognition In Action/9. Dealing with Zero Variances.mp4
47.9MB
13. Performance Optimization/1. Handing Large Datasets.mp4
44.46MB
13. Performance Optimization/10. Tensorflow's Eager Memory Usage.mp4
46.81MB
13. Performance Optimization/11. Cleaning up Tensors with Tidy.mp4
24.26MB
13. Performance Optimization/12. Implementing TF Tidy.mp4
37.6MB
13. Performance Optimization/13. Tidying the Training Loop.mp4
45.99MB
13. Performance Optimization/14. Measuring Reduced Memory Usage.mp4
18.11MB
13. Performance Optimization/15. One More Optimization.mp4
27.5MB
13. Performance Optimization/16. Final Memory Report.mp4
36.25MB
13. Performance Optimization/17. Plotting Cost History.mp4
47.6MB
13. Performance Optimization/18. NaN in Cost History.mp4
46.38MB
13. Performance Optimization/19. Fixing Cost History.mp4
46.77MB
13. Performance Optimization/2. Minimizing Memory Usage.mp4
38.19MB
13. Performance Optimization/20. Massaging Learning Parameters.mp4
22.55MB
13. Performance Optimization/21. Improving Model Accuracy.mp4
55.02MB
13. Performance Optimization/3. Creating Memory Snapshots.mp4
49.06MB
13. Performance Optimization/4. The Javascript Garbage Collector.mp4
55.8MB
13. Performance Optimization/5. Shallow vs Retained Memory Usage.mp4
56.89MB
13. Performance Optimization/6. Measuring Memory Usage.mp4
96.63MB
13. Performance Optimization/7. Releasing References.mp4
35.98MB
13. Performance Optimization/8. Measuring Footprint Reduction.mp4
43.31MB
13. Performance Optimization/9. Optimization Tensorflow Memory Usage.mp4
18.54MB
14. Appendix Custom CSV Loader/1. Loading CSV Files.mp4
15.86MB
14. Appendix Custom CSV Loader/10. Splitting Test and Training.mp4
75.65MB
14. Appendix Custom CSV Loader/2. A Test Dataset.mp4
9.58MB
14. Appendix Custom CSV Loader/3. Reading Files from Disk.mp4
18.6MB
14. Appendix Custom CSV Loader/4. Splitting into Columns.mp4
20.34MB
14. Appendix Custom CSV Loader/5. Dropping Trailing Columns.mp4
18.4MB
14. Appendix Custom CSV Loader/6. Parsing Number Values.mp4
31.36MB
14. Appendix Custom CSV Loader/7. Custom Value Parsing.mp4
36.73MB
14. Appendix Custom CSV Loader/8. Extracting Data Columns.mp4
57.27MB
14. Appendix Custom CSV Loader/9. Shuffling Data via Seed Phrase.mp4
52.14MB
2. Algorithm Overview/1. How K-Nearest Neighbor Works.mp4
93.33MB
2. Algorithm Overview/10. Gauging Accuracy.mp4
54.02MB
2. Algorithm Overview/11. Printing a Report.mp4
33.3MB
2. Algorithm Overview/12. Refactoring Accuracy Reporting.mp4
52.3MB
2. Algorithm Overview/13. Investigating Optimal K Values.mp4
129.14MB
2. Algorithm Overview/14. Updating KNN for Multiple Features.mp4
70.61MB
2. Algorithm Overview/15. Multi-Dimensional KNN.mp4
44.2MB
2. Algorithm Overview/16. N-Dimension Distance.mp4
78.87MB
2. Algorithm Overview/17. Arbitrary Feature Spaces.mp4
71.25MB
2. Algorithm Overview/18. Magnitude Offsets in Features.mp4
64.06MB
2. Algorithm Overview/19. Feature Normalization.mp4
72.92MB
2. Algorithm Overview/2. Lodash Review.mp4
64.93MB
2. Algorithm Overview/20. Normalization with MinMax.mp4
67.04MB
2. Algorithm Overview/21. Applying Normalization.mp4
45.35MB
2. Algorithm Overview/22. Feature Selection with KNN.mp4
80.37MB
2. Algorithm Overview/23. Objective Feature Picking.mp4
65.97MB
2. Algorithm Overview/24. Evaluating Different Feature Values.mp4
27.97MB
2. Algorithm Overview/3. Implementing KNN.mp4
59.34MB
2. Algorithm Overview/4. Finishing KNN Implementation.mp4
50.28MB
2. Algorithm Overview/5. Testing the Algorithm.mp4
44.97MB
2. Algorithm Overview/6. Interpreting Bad Results.mp4
40.75MB
2. Algorithm Overview/7. Test and Training Data.mp4
45.2MB
2. Algorithm Overview/8. Randomizing Test Data.mp4
36.01MB
2. Algorithm Overview/9. Generalizing KNN.mp4
39MB
3. Onwards to Tensorflow JS!/1. Let's Get Our Bearings.mp4
76.62MB
3. Onwards to Tensorflow JS!/10. Creating Slices of Data.mp4
58.91MB
3. Onwards to Tensorflow JS!/11. Tensor Concatenation.mp4
44.13MB
3. Onwards to Tensorflow JS!/12. Summing Values Along an Axis.mp4
41.36MB
3. Onwards to Tensorflow JS!/13. Massaging Dimensions with ExpandDims.mp4
57.02MB
3. Onwards to Tensorflow JS!/2. A Plan to Move Forward.mp4
48.65MB
3. Onwards to Tensorflow JS!/3. Tensor Shape and Dimension.mp4
114.28MB
3. Onwards to Tensorflow JS!/5. Elementwise Operations.mp4
58.36MB
3. Onwards to Tensorflow JS!/6. Broadcasting Operations.mp4
62.06MB
3. Onwards to Tensorflow JS!/8. Logging Tensor Data.mp4
26MB
3. Onwards to Tensorflow JS!/9. Tensor Accessors.mp4
30.47MB
4. Applications of Tensorflow/1. KNN with Regression.mp4
54.99MB
4. Applications of Tensorflow/10. Reporting Error Percentages.mp4
64.5MB
4. Applications of Tensorflow/11. Normalization or Standardization.mp4
92.98MB
4. Applications of Tensorflow/12. Numerical Standardization with Tensorflow.mp4
53.05MB
4. Applications of Tensorflow/13. Applying Standardization.mp4
41.46MB
4. Applications of Tensorflow/14. Debugging Calculations.mp4
86.71MB
4. Applications of Tensorflow/15. What Now.mp4
42.33MB
4. Applications of Tensorflow/2. A Change in Data Structure.mp4
41.35MB
4. Applications of Tensorflow/3. KNN with Tensorflow.mp4
78.71MB
4. Applications of Tensorflow/4. Maintaining Order Relationships.mp4
57.75MB
4. Applications of Tensorflow/5. Sorting Tensors.mp4
62.85MB
4. Applications of Tensorflow/6. Averaging Top Values.mp4
58.13MB
4. Applications of Tensorflow/7. Moving to the Editor.mp4
34.34MB
4. Applications of Tensorflow/8. Loading CSV Data.mp4
89.33MB
4. Applications of Tensorflow/9. Running an Analysis.mp4
52.5MB
5. Getting Started with Gradient Descent/1. Linear Regression.mp4
25.38MB
5. Getting Started with Gradient Descent/10. Answering Common Questions.mp4
40.94MB
5. Getting Started with Gradient Descent/11. Gradient Descent with Multiple Terms.mp4
44.2MB
5. Getting Started with Gradient Descent/12. Multiple Terms in Action.mp4
123.16MB
5. Getting Started with Gradient Descent/2. Why Linear Regression.mp4
50.34MB
5. Getting Started with Gradient Descent/3. Understanding Gradient Descent.mp4
126.77MB
5. Getting Started with Gradient Descent/4. Guessing Coefficients with MSE.mp4
93.47MB
5. Getting Started with Gradient Descent/5. Observations Around MSE.mp4
56.12MB
5. Getting Started with Gradient Descent/6. Derivatives!.mp4
77.95MB
5. Getting Started with Gradient Descent/7. Gradient Descent in Action.mp4
115.36MB
5. Getting Started with Gradient Descent/8. Quick Breather and Review.mp4
65.79MB
5. Getting Started with Gradient Descent/9. Why a Learning Rate.mp4
187.28MB
6. Gradient Descent with Tensorflow/1. Project Overview.mp4
57.05MB
6. Gradient Descent with Tensorflow/10. More on Matrix Multiplication.mp4
63.25MB
6. Gradient Descent with Tensorflow/11. Matrix Form of Slope Equations.mp4
59.61MB
6. Gradient Descent with Tensorflow/12. Simplification with Matrix Multiplication.mp4
90.79MB
6. Gradient Descent with Tensorflow/13. How it All Works Together!.mp4
143.82MB
6. Gradient Descent with Tensorflow/2. Data Loading.mp4
43.49MB
6. Gradient Descent with Tensorflow/3. Default Algorithm Options.mp4
62.66MB
6. Gradient Descent with Tensorflow/4. Formulating the Training Loop.mp4
27.68MB
6. Gradient Descent with Tensorflow/5. Initial Gradient Descent Implementation.mp4
87.93MB
6. Gradient Descent with Tensorflow/6. Calculating MSE Slopes.mp4
67.14MB
6. Gradient Descent with Tensorflow/7. Updating Coefficients.mp4
33.86MB
6. Gradient Descent with Tensorflow/8. Interpreting Results.mp4
101.72MB
6. Gradient Descent with Tensorflow/9. Matrix Multiplication.mp4
67.46MB
7. Increasing Performance with Vectorized Solutions/1. Refactoring the Linear Regression Class.mp4
72.71MB
7. Increasing Performance with Vectorized Solutions/10. Reapplying Standardization.mp4
57.96MB
7. Increasing Performance with Vectorized Solutions/11. Fixing Standardization Issues.mp4
47.84MB
7. Increasing Performance with Vectorized Solutions/12. Massaging Learning Rates.mp4
36.45MB
7. Increasing Performance with Vectorized Solutions/13. Moving Towards Multivariate Regression.mp4
121.42MB
7. Increasing Performance with Vectorized Solutions/14. Refactoring for Multivariate Analysis.mp4
82.36MB
7. Increasing Performance with Vectorized Solutions/15. Learning Rate Optimization.mp4
76.69MB
7. Increasing Performance with Vectorized Solutions/16. Recording MSE History.mp4
51.95MB
7. Increasing Performance with Vectorized Solutions/17. Updating Learning Rate.mp4
62.15MB
7. Increasing Performance with Vectorized Solutions/2. Refactoring to One Equation.mp4
84.8MB
7. Increasing Performance with Vectorized Solutions/3. A Few More Changes.mp4
66.17MB
7. Increasing Performance with Vectorized Solutions/4. Same Results Or Not.mp4
33.83MB
7. Increasing Performance with Vectorized Solutions/5. Calculating Model Accuracy.mp4
80.37MB
7. Increasing Performance with Vectorized Solutions/6. Implementing Coefficient of Determination.mp4
75.79MB
7. Increasing Performance with Vectorized Solutions/7. Dealing with Bad Accuracy.mp4
71.41MB
7. Increasing Performance with Vectorized Solutions/8. Reminder on Standardization.mp4
44.49MB
7. Increasing Performance with Vectorized Solutions/9. Data Processing in a Helper Method.mp4
37.17MB
8. Plotting Data with Javascript/1. Observing Changing Learning Rate and MSE.mp4
45.83MB
8. Plotting Data with Javascript/2. Plotting MSE Values.mp4
61.4MB
8. Plotting Data with Javascript/3. Plotting MSE History against B Values.mp4
47.81MB
9. Gradient Descent Alterations/1. Batch and Stochastic Gradient Descent.mp4
77.24MB
9. Gradient Descent Alterations/2. Refactoring Towards Batch Gradient Descent.mp4
55.11MB
9. Gradient Descent Alterations/3. Determining Batch Size and Quantity.mp4
66.09MB
9. Gradient Descent Alterations/4. Iterating Over Batches.mp4
67.45MB
9. Gradient Descent Alterations/5. Evaluating Batch Gradient Descent Results.mp4
66.23MB
9. Gradient Descent Alterations/6. Making Predictions with the Model.mp4
79.5MB
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