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Title: UDEMY Machine Learning and AI Support Vector Machines in Python FTUGroup: NOGRPSource: Udemy
Info Hash
1DCA37E8DB24F33437B3E2E63A250099AC69B11C
Source
Unverified
Total Size
3.05 GB
Total Files
100
Seeders
0
Leechers
1
Health
Score
1
Type
Bookware

File List

FileSize
1. Welcome/1. Introduction.mp416.15 MB
1. Welcome/1. Introduction.vtt2.69 KB
1. Welcome/2. Course Objectives.mp437.24 MB
1. Welcome/2. Course Objectives.vtt5.72 KB
1. Welcome/3. Course Outline.mp431.3 MB
1. Welcome/3. Course Outline.vtt6.68 KB
1. Welcome/4. Where to get the code and data.mp439.03 MB
1. Welcome/4. Where to get the code and data.vtt6.98 KB
2. Beginner_s Corner/1. Beginner_s Corner Section Introduction.mp434.01 MB
2. Beginner_s Corner/1. Beginner_s Corner Section Introduction.vtt6.23 KB
2. Beginner_s Corner/2. Image Classification with SVMs.mp436.49 MB
2. Beginner_s Corner/2. Image Classification with SVMs.vtt6.37 KB
2. Beginner_s Corner/3. Spam Detection with SVMs.mp4101.47 MB
2. Beginner_s Corner/3. Spam Detection with SVMs.vtt12.42 KB
2. Beginner_s Corner/4. Medical Diagnosis with SVMs.mp447.91 MB
2. Beginner_s Corner/4. Medical Diagnosis with SVMs.vtt6.05 KB
2. Beginner_s Corner/5. Regression with SVMs.mp450.9 MB
2. Beginner_s Corner/5. Regression with SVMs.vtt5.63 KB
2. Beginner_s Corner/6. Cross-Validation.mp454.63 MB
2. Beginner_s Corner/6. Cross-Validation.vtt8.33 KB
2. Beginner_s Corner/7. How do you get the data How do you process the data.mp428.83 MB
2. Beginner_s Corner/7. How do you get the data How do you process the data.vtt6.68 KB
3. Review of Linear Classifiers/1. Basic Geometry.mp446.61 MB
3. Review of Linear Classifiers/1. Basic Geometry.vtt11.41 KB
3. Review of Linear Classifiers/2. Normal Vectors.mp414.8 MB
3. Review of Linear Classifiers/2. Normal Vectors.vtt3.64 KB
3. Review of Linear Classifiers/3. Logistic Regression Review.mp439.9 MB
3. Review of Linear Classifiers/3. Logistic Regression Review.vtt10.69 KB
3. Review of Linear Classifiers/4. Loss Function and Regularization.mp416.15 MB
3. Review of Linear Classifiers/4. Loss Function and Regularization.vtt4.3 KB
3. Review of Linear Classifiers/5. Prediction Confidence.mp430.65 MB
3. Review of Linear Classifiers/5. Prediction Confidence.vtt7.92 KB
3. Review of Linear Classifiers/6. Nonlinear Problems.mp447.05 MB
3. Review of Linear Classifiers/6. Nonlinear Problems.vtt10.41 KB
3. Review of Linear Classifiers/7. Linear Classifiers Section Conclusion.mp419.29 MB
3. Review of Linear Classifiers/7. Linear Classifiers Section Conclusion.vtt4.69 KB
4. Linear SVM/10. Linear SVM Section Summary.mp418.99 MB
4. Linear SVM/10. Linear SVM Section Summary.vtt4.88 KB
4. Linear SVM/1. Linear SVM Section Introduction and Outline.mp417.68 MB
4. Linear SVM/1. Linear SVM Section Introduction and Outline.vtt3.74 KB
4. Linear SVM/2. Linear SVM Problem Setup and Definitions.mp422.84 MB
4. Linear SVM/2. Linear SVM Problem Setup and Definitions.vtt5.11 KB
4. Linear SVM/3. Margins.mp441.49 MB
4. Linear SVM/3. Margins.vtt8.56 KB
4. Linear SVM/4. Linear SVM Objective.mp449.17 MB
4. Linear SVM/4. Linear SVM Objective.vtt11.64 KB
4. Linear SVM/5. Linear and Quadratic Programming.mp464.22 MB
4. Linear SVM/5. Linear and Quadratic Programming.vtt13.19 KB
4. Linear SVM/6. Slack Variables.mp438.68 MB
4. Linear SVM/6. Slack Variables.vtt7.95 KB
4. Linear SVM/7. Hinge Loss (and its Relationship to Logistic Regression).mp429.69 MB
4. Linear SVM/7. Hinge Loss (and its Relationship to Logistic Regression).vtt6.68 KB
4. Linear SVM/8. Linear SVM with Gradient Descent.mp415.68 MB
4. Linear SVM/8. Linear SVM with Gradient Descent.vtt3.13 KB
4. Linear SVM/9. Linear SVM with Gradient Descent (Code).mp451.93 MB
4. Linear SVM/9. Linear SVM with Gradient Descent (Code).vtt5.31 KB
5. Duality/1. Duality Section Introduction.mp414.72 MB
5. Duality/1. Duality Section Introduction.vtt4.22 KB
5. Duality/2. Duality and Lagrangians (part 1).mp458.69 MB
5. Duality/2. Duality and Lagrangians (part 1).vtt13.63 KB
5. Duality/3. Lagrangian Duality (part 2).mp429.19 MB
5. Duality/3. Lagrangian Duality (part 2).vtt6.74 KB
5. Duality/4. Relationship to Linear Programming.mp420.12 MB
5. Duality/4. Relationship to Linear Programming.vtt4.55 KB
5. Duality/5. Predictions and Support Vectors.mp438.88 MB
5. Duality/5. Predictions and Support Vectors.vtt9.57 KB
5. Duality/6. Why Transform Primal to Dual.mp416.93 MB
5. Duality/6. Why Transform Primal to Dual.vtt3.75 KB
5. Duality/7. Duality Section Conclusion.mp413.22 MB
5. Duality/7. Duality Section Conclusion.vtt2.99 KB
6. Kernel Methods/1. Kernel Methods Section Introduction.mp419.13 MB
6. Kernel Methods/1. Kernel Methods Section Introduction.vtt3.87 KB
6. Kernel Methods/2. The Kernel Trick.mp437.25 MB
6. Kernel Methods/2. The Kernel Trick.vtt8.03 KB
6. Kernel Methods/3. Polynomial Kernel.mp425.37 MB
6. Kernel Methods/3. Polynomial Kernel.vtt5.91 KB
6. Kernel Methods/4. Gaussian Kernel.mp426.96 MB
6. Kernel Methods/4. Gaussian Kernel.vtt5.26 KB
6. Kernel Methods/5. Using the Gaussian Kernel.mp436.01 MB
6. Kernel Methods/5. Using the Gaussian Kernel.vtt7.64 KB
6. Kernel Methods/6. Why does the Gaussian Kernel correspond to infinite-dimensional features.mp419.85 MB
6. Kernel Methods/6. Why does the Gaussian Kernel correspond to infinite-dimensional features.vtt4.4 KB
6. Kernel Methods/7. Other Kernels.mp432.44 MB
6. Kernel Methods/7. Other Kernels.vtt7.23 KB
6. Kernel Methods/8. Mercer_s Condition.mp427.57 MB
6. Kernel Methods/8. Mercer_s Condition.vtt6.57 KB
6. Kernel Methods/9. Kernel Methods Section Summary.mp411.14 MB
6. Kernel Methods/9. Kernel Methods Section Summary.vtt2.82 KB
7. Implementations and Extensions/1. Dual with Slack Variables.mp438.93 MB
7. Implementations and Extensions/1. Dual with Slack Variables.vtt11.2 KB
7. Implementations and Extensions/2. Simple Approaches to Implementation.mp424.65 MB
7. Implementations and Extensions/2. Simple Approaches to Implementation.vtt6.93 KB
7. Implementations and Extensions/3. SVM with Projected Gradient Descent Code.mp483.6 MB
7. Implementations and Extensions/3. SVM with Projected Gradient Descent Code.vtt7.8 KB
7. Implementations and Extensions/4. Kernel SVM Gradient Descent with Primal (Theory).mp421.35 MB
7. Implementations and Extensions/4. Kernel SVM Gradient Descent with Primal (Theory).vtt4.89 KB
7. Implementations and Extensions/5. Kernel SVM Gradient Descent with Primal (Code).mp458.72 MB
7. Implementations and Extensions/5. Kernel SVM Gradient Descent with Primal (Code).vtt4.09 KB
7. Implementations and Extensions/6. SMO (Sequential Minimal Optimization).mp441.42 MB
7. Implementations and Extensions/6. SMO (Sequential Minimal Optimization).vtt10.54 KB

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