[UdemyCourseDownloader] Machine Learning Practical 6 Real-World Applications

Creation Time	March 3, 2024, 1:34 p.m.
Last Access Time	Feb. 23, 2025, 4:25 p.m.
File Size	4.0 GB
Keywords	UdemyCourseDownloader Practical Real-World Machine Applications Learning 6
Total Requests	19
Total Files	160
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2. Breast Cancer Classification/8. Improving the Model.mp4 189.8 MB
2. Breast Cancer Classification/5. Data Visualisation.mp4 140.5 MB
3. Fashion Class Classification/3. Data Visualisation.mp4 130.1 MB
3. Fashion Class Classification/7. Model Training Part IV.mp4 128.2 MB
3. Fashion Class Classification/6. Model Training Part III.mp4 126.0 MB
3. Fashion Class Classification/4. Model Training Part I.mp4 103.8 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/2. Data.mp4 101.9 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/12. Grid Search Part 2.mp4 98.1 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/10. Model Building Part 2.mp4 93.5 MB
3. Fashion Class Classification/1. Business Challenge.mp4 92.2 MB
2. Breast Cancer Classification/7. Model Evaluation.mp4 91.4 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/9. Feature Scaling & Balancing.mp4 79.7 MB
2. Breast Cancer Classification/4. Challenge in Machine Learning Vocabulary.mp4 79.1 MB
3. Fashion Class Classification/5. Model Training Part II.mp4 78.3 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/2. Data.mp4 77.5 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/1. Introduction.mp4 75.1 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/11. Grid Search Part 1.mp4 74.4 MB
3. Fashion Class Classification/8. Model Evaluation.mp4 73.6 MB
4. Directing Customers to Subscription Through App Behavior Analysis/10. Model Building.mp4 72.3 MB
4. Directing Customers to Subscription Through App Behavior Analysis/8. Feature Engineering - Screens.mp4 71.0 MB
2. Breast Cancer Classification/6. Model Training.mp4 70.9 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/5. Pie Chart Distributions.mp4 70.6 MB
3. Fashion Class Classification/2. Challenge in Machine Learning Vocabulary.mp4 69.2 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/12. Feature Selection.mp4 64.3 MB
2. Breast Cancer Classification/2. Business Challenge.mp4 61.0 MB
4. Directing Customers to Subscription Through App Behavior Analysis/4. Features Histograms.mp4 60.8 MB
4. Directing Customers to Subscription Through App Behavior Analysis/9. Data Pre-Processing.mp4 60.7 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/8. Data Preprocessing.mp4 60.2 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/9. Model Building Part 1.mp4 58.8 MB
2. Breast Cancer Classification/3. Updates on Udemy Reviews.mp4 56.1 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/7. Correlation Matrix.mp4 56.1 MB
3. Fashion Class Classification/10. Conclusion.mp4 55.3 MB
4. Directing Customers to Subscription Through App Behavior Analysis/7. Feature Engineering - Response.mp4 54.9 MB
4. Directing Customers to Subscription Through App Behavior Analysis/3. Data.mp4 53.6 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/10. Model Building.mp4 51.3 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/4. Histograms.mp4 50.8 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/4. Features Histograms.mp4 50.2 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/6. Correlation Plot.mp4 48.7 MB
7. Credit Card Fraud Detection/7. Deep Learning Part 2.mp4 48.2 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/3. Data Housekeeping.mp4 44.1 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/8. One-Hot Encoding.mp4 42.9 MB
7. Credit Card Fraud Detection/11. Confusion Matrix.mp4 40.1 MB
7. Credit Card Fraud Detection/5. Data Preprocessing.mp4 39.0 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/13. Model Conclusion.mp4 38.4 MB
7. Credit Card Fraud Detection/8. Splitting the Data.mp4 38.2 MB
7. Credit Card Fraud Detection/16. Undersampling.mp4 36.9 MB
1. Introduction/1. Welcome to the course!.mp4 36.7 MB
7. Credit Card Fraud Detection/17. Smote.mp4 35.7 MB
7. Credit Card Fraud Detection/12. Machine Learning Classifiers.mp4 34.2 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/6. Correlation Matrix.mp4 33.4 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/3. Data Cleaning.mp4 32.6 MB
4. Directing Customers to Subscription Through App Behavior Analysis/6. Correlation Matrix.mp4 32.3 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/11. K-Fold Cross Validation.mp4 31.7 MB
3. Fashion Class Classification/9. Improving the Model.mp4 31.6 MB
7. Credit Card Fraud Detection/13. Random Forest.mp4 31.0 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/14. Final Remarks.mp4 30.6 MB
7. Credit Card Fraud Detection/1. Case Study.mp4 30.1 MB
4. Directing Customers to Subscription Through App Behavior Analysis/11. Model Conclusion.mp4 30.0 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/14. Final Remarks.mp4 24.3 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/5. Correlation Plot.mp4 24.3 MB
2. Breast Cancer Classification/9. Conclusion.mp4 24.0 MB
7. Credit Card Fraud Detection/3. Set Up.mp4 23.9 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/7. Feature Engineering.mp4 23.5 MB
7. Credit Card Fraud Detection/6. Deep Learning Part 1.mp4 23.2 MB
7. Credit Card Fraud Detection/2. Machine Learning Vocabulary.mp4 22.9 MB
4. Directing Customers to Subscription Through App Behavior Analysis/5. Correlation Plot.mp4 22.0 MB
7. Credit Card Fraud Detection/9. Training.mp4 21.2 MB
7. Credit Card Fraud Detection/4. Data Visualization.mp4 20.4 MB
5. Minimizing Churn Rate Through Analysis of Financial Habits/1. Introduction.mp4 19.6 MB
7. Credit Card Fraud Detection/18. Final remarks.mp4 19.1 MB
4. Directing Customers to Subscription Through App Behavior Analysis/12. Final Remarks.mp4 19.0 MB
7. Credit Card Fraud Detection/14. Decision Trees.mp4 18.8 MB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/13. Model Conclusion.mp4 18.3 MB
4. Directing Customers to Subscription Through App Behavior Analysis/2. Introduction.mp4 18.3 MB
7. Credit Card Fraud Detection/10. Metrics.mp4 15.1 MB
2. Breast Cancer Classification/1. Introduction.mp4 15.0 MB
4. Directing Customers to Subscription Through App Behavior Analysis/1. Fintech Case Studies Introduction.mp4 14.6 MB
7. Credit Card Fraud Detection/15. Sampling.mp4 7.7 MB
2. Breast Cancer Classification/8. Improving the Model.vtt 29.1 KB
2. Breast Cancer Classification/5. Data Visualisation.vtt 23.0 KB
3. Fashion Class Classification/3. Data Visualisation.vtt 19.9 KB
3. Fashion Class Classification/7. Model Training Part IV.vtt 19.4 KB
3. Fashion Class Classification/6. Model Training Part III.vtt 14.4 KB
2. Breast Cancer Classification/7. Model Evaluation.vtt 14.4 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/11. Grid Search Part 1.vtt 14.0 KB
4. Directing Customers to Subscription Through App Behavior Analysis/10. Model Building.vtt 13.0 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/4. Histograms.vtt 12.6 KB
3. Fashion Class Classification/8. Model Evaluation.vtt 12.2 KB
3. Fashion Class Classification/4. Model Training Part I.vtt 11.8 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/7. Correlation Matrix.vtt 11.7 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/10. Model Building Part 2.vtt 11.6 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/12. Grid Search Part 2.vtt 11.2 KB
2. Breast Cancer Classification/6. Model Training.vtt 11.0 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/8. Data Preprocessing.vtt 11.0 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/9. Feature Scaling & Balancing.vtt 10.9 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/4. Features Histograms.vtt 10.7 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/5. Pie Chart Distributions.vtt 10.7 KB
4. Directing Customers to Subscription Through App Behavior Analysis/8. Feature Engineering - Screens.vtt 10.3 KB
3. Fashion Class Classification/5. Model Training Part II.vtt 10.1 KB
2. Breast Cancer Classification/4. Challenge in Machine Learning Vocabulary.vtt 10.0 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/2. Data.vtt 9.8 KB
4. Directing Customers to Subscription Through App Behavior Analysis/9. Data Pre-Processing.vtt 9.8 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/2. Data.vtt 9.8 KB
4. Directing Customers to Subscription Through App Behavior Analysis/4. Features Histograms.vtt 9.7 KB
4. Directing Customers to Subscription Through App Behavior Analysis/7. Feature Engineering - Response.vtt 9.7 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/1. Introduction.vtt 9.6 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/10. Model Building.vtt 9.5 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/6. Correlation Plot.vtt 9.4 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/6. Correlation Matrix.vtt 9.1 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/12. Feature Selection.vtt 8.7 KB
3. Fashion Class Classification/2. Challenge in Machine Learning Vocabulary.vtt 8.4 KB
4. Directing Customers to Subscription Through App Behavior Analysis/6. Correlation Matrix.vtt 8.3 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/9. Model Building Part 1.vtt 8.0 KB
7. Credit Card Fraud Detection/12. Machine Learning Classifiers.vtt 7.7 KB
7. Credit Card Fraud Detection/7. Deep Learning Part 2.vtt 7.4 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/3. Data Housekeeping.vtt 6.9 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/5. Correlation Plot.vtt 6.6 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/7. Feature Engineering.vtt 6.6 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/8. One-Hot Encoding.vtt 6.5 KB
3. Fashion Class Classification/1. Business Challenge.vtt 5.8 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/3. Data Cleaning.vtt 5.7 KB
4. Directing Customers to Subscription Through App Behavior Analysis/5. Correlation Plot.vtt 5.5 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/13. Model Conclusion.vtt 5.3 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/11. K-Fold Cross Validation.vtt 5.2 KB
3. Fashion Class Classification/10. Conclusion.vtt 4.6 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/14. Final Remarks.vtt 4.1 KB
7. Credit Card Fraud Detection/8. Splitting the Data.vtt 4.1 KB
4. Directing Customers to Subscription Through App Behavior Analysis/11. Model Conclusion.vtt 4.1 KB
4. Directing Customers to Subscription Through App Behavior Analysis/3. Data.vtt 4.1 KB
7. Credit Card Fraud Detection/11. Confusion Matrix.vtt 4.0 KB
7. Credit Card Fraud Detection/10. Metrics.vtt 4.0 KB
2. Breast Cancer Classification/2. Business Challenge.vtt 3.7 KB
2. Breast Cancer Classification/9. Conclusion.vtt 3.6 KB
2. Breast Cancer Classification/3. Updates on Udemy Reviews.vtt 3.5 KB
7. Credit Card Fraud Detection/1. Case Study.vtt 3.5 KB
3. Fashion Class Classification/9. Improving the Model.vtt 3.5 KB
7. Credit Card Fraud Detection/6. Deep Learning Part 1.vtt 3.4 KB
6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/13. Model Conclusion.vtt 3.4 KB
7. Credit Card Fraud Detection/2. Machine Learning Vocabulary.vtt 3.3 KB
7. Credit Card Fraud Detection/3. Set Up.vtt 3.3 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/14. Final Remarks.vtt 3.1 KB
7. Credit Card Fraud Detection/13. Random Forest.vtt 3.1 KB
7. Credit Card Fraud Detection/18. Final remarks.vtt 3.1 KB
7. Credit Card Fraud Detection/5. Data Preprocessing.vtt 2.9 KB
7. Credit Card Fraud Detection/14. Decision Trees.vtt 2.6 KB
7. Credit Card Fraud Detection/16. Undersampling.vtt 2.6 KB
5. Minimizing Churn Rate Through Analysis of Financial Habits/1. Introduction.vtt 2.5 KB
7. Credit Card Fraud Detection/17. Smote.vtt 2.5 KB
4. Directing Customers to Subscription Through App Behavior Analysis/12. Final Remarks.vtt 2.4 KB
7. Credit Card Fraud Detection/4. Data Visualization.vtt 2.4 KB
1. Introduction/1. Welcome to the course!.vtt 2.3 KB
4. Directing Customers to Subscription Through App Behavior Analysis/2. Introduction.vtt 2.3 KB
7. Credit Card Fraud Detection/15. Sampling.vtt 2.1 KB
4. Directing Customers to Subscription Through App Behavior Analysis/1. Fintech Case Studies Introduction.vtt 2.0 KB
7. Credit Card Fraud Detection/9. Training.vtt 1.9 KB
[FTU Forum].url 1.3 KB
2. Breast Cancer Classification/1. Introduction.vtt 1.0 KB
[FreeCoursesOnline.Me].url 133 bytes
[FreeTutorials.Eu].url 129 bytes
1. Introduction/2. Where to get the materials.html 128 bytes

[UdemyCourseDownloader] Machine Learning Practical 6 Real-World Applications

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