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[FreeCourseSite.com] Udemy - Machine Learning with Imbalanced Data
magnet:?xt=urn:btih:3b0af3c432a8688ab0e4c39969d7994950063be3&dn=[FreeCourseSite.com] Udemy - Machine Learning with Imbalanced Data
磁力链接详情
Hash值:
3b0af3c432a8688ab0e4c39969d7994950063be3
点击数:
112
文件大小:
2.9 GB
文件数量:
109
创建日期:
2022-11-9 08:42
最后访问:
2024-7-15 05:32
访问标签:
FreeCourseSite
com
Udemy
-
Machine
Learning
with
Imbalanced
Data
文件列表详情
01 - Introduction/001 Course Curriculum Overview.mp4 17.5 MB
01 - Introduction/002 Course Material.mp4 9.21 MB
02 - Machine Learning with Imbalanced Data Overview/001 Imbalanced classes - Introduction.mp4 25.5 MB
02 - Machine Learning with Imbalanced Data Overview/002 Nature of the imbalanced class.mp4 24.81 MB
02 - Machine Learning with Imbalanced Data Overview/003 Approaches to work with imbalanced datasets - Overview.mp4 12.13 MB
03 - Evaluation Metrics/001 Introduction to Performance Metrics.mp4 6.78 MB
03 - Evaluation Metrics/002 Accuracy.mp4 11.38 MB
03 - Evaluation Metrics/003 Accuracy - Demo.mp4 39.61 MB
03 - Evaluation Metrics/004 Precision, Recall and F-measure.mp4 30.24 MB
03 - Evaluation Metrics/006 Precision, Recall and F-measure - Demo.mp4 76.09 MB
03 - Evaluation Metrics/007 Confusion tables, FPR and FNR.mp4 15.4 MB
03 - Evaluation Metrics/008 Confusion tables, FPR and FNR - Demo.mp4 45.98 MB
03 - Evaluation Metrics/009 Balanced Accuracy.mp4 7.75 MB
03 - Evaluation Metrics/010 Balanced accuracy - Demo.mp4 16.55 MB
03 - Evaluation Metrics/011 Geometric Mean, Dominance, Index of Imbalanced Accuracy.mp4 11.89 MB
03 - Evaluation Metrics/012 Geometric Mean, Dominance, Index of Imbalanced Accuracy - Demo.mp4 74.3 MB
03 - Evaluation Metrics/013 ROC-AUC.mp4 34.31 MB
03 - Evaluation Metrics/014 ROC-AUC - Demo.mp4 29.63 MB
03 - Evaluation Metrics/015 Precision-Recall Curve.mp4 15.8 MB
03 - Evaluation Metrics/016 Precision-Recall Curve - Demo.mp4 18.11 MB
03 - Evaluation Metrics/019 Probability.mp4 10.11 MB
03 - Evaluation Metrics/020 Metrics for Mutliclass.mp4 26.18 MB
03 - Evaluation Metrics/021 Metrics for Multiclass - Demo.mp4 51.95 MB
03 - Evaluation Metrics/022 PR and ROC Curves for Multiclass.mp4 11.34 MB
03 - Evaluation Metrics/023 PR Curves in Multiclass - Demo.mp4 54.74 MB
03 - Evaluation Metrics/024 ROC Curve in Multiclass - Demo.mp4 46.07 MB
04 - Udersampling/001 Under-Sampling Methods - Introduction.mp4 31.55 MB
04 - Udersampling/002 Random Under-Sampling - Intro.mp4 10.68 MB
04 - Udersampling/003 Random Under-Sampling - Demo.mp4 58.66 MB
04 - Udersampling/004 Condensed Nearest Neighbours - Intro.mp4 37.56 MB
04 - Udersampling/005 Condensed Nearest Neighbours - Demo.mp4 50.03 MB
04 - Udersampling/006 Tomek Links - Intro.mp4 9.75 MB
04 - Udersampling/007 Tomek Links - Demo.mp4 16.15 MB
04 - Udersampling/008 One Sided Selection - Intro.mp4 9.89 MB
04 - Udersampling/009 One Sided Selection - Demo.mp4 16.12 MB
04 - Udersampling/010 Edited Nearest Neighbours - Intro.mp4 23.49 MB
04 - Udersampling/011 Edited Nearest Neighbours - Demo.mp4 26.35 MB
04 - Udersampling/012 Repeated Edited Nearest Neighbours - Intro.mp4 13.68 MB
04 - Udersampling/013 Repeated Edited Nearest Neighbours - Demo.mp4 19.74 MB
04 - Udersampling/014 All KNN - Intro.mp4 13.74 MB
04 - Udersampling/015 All KNN - Demo.mp4 36.12 MB
04 - Udersampling/016 Neighbourhood Cleaning Rule - Intro.mp4 14.35 MB
04 - Udersampling/017 Neighbourhood Cleaning Rule - Demo.mp4 12.47 MB
04 - Udersampling/018 NearMiss - Intro.mp4 13.83 MB
04 - Udersampling/019 NearMiss - Demo.mp4 18.97 MB
04 - Udersampling/020 Instance Hardness Threshold - Intro.mp4 20.53 MB
04 - Udersampling/021 Instance Hardness Threshold - Demo.mp4 102.59 MB
04 - Udersampling/022 Instance Hardness Threshold Multiclass Demo.mp4 48.3 MB
04 - Udersampling/023 Undersampling Method Comparison.mp4 41.11 MB
04 - Udersampling/024 Wrapping up the section.mp4 11.7 MB
04 - Udersampling/025 Setting up a classifier with under-sampling and cross-validation.mp4 63.88 MB
05 - Oversampling/001 Over-Sampling Methods - Introduction.mp4 10.64 MB
05 - Oversampling/002 Random Over-Sampling.mp4 21.41 MB
05 - Oversampling/003 Random Over-Sampling - Demo.mp4 26.16 MB
05 - Oversampling/004 ROS with smoothing - Intro.mp4 23.35 MB
05 - Oversampling/005 ROS with smoothing - Demo.mp4 23.41 MB
05 - Oversampling/006 SMOTE.mp4 44.61 MB
05 - Oversampling/007 SMOTE - Demo.mp4 17.46 MB
05 - Oversampling/008 SMOTE-NC.mp4 20.48 MB
05 - Oversampling/009 SMOTE-NC - Demo.mp4 18.36 MB
05 - Oversampling/010 SMOTE-N.mp4 45.36 MB
05 - Oversampling/011 SMOTE-N Demo.mp4 44.8 MB
05 - Oversampling/012 ADASYN.mp4 25.24 MB
05 - Oversampling/013 ADASYN - Demo.mp4 15.62 MB
05 - Oversampling/014 Borderline SMOTE.mp4 34.42 MB
05 - Oversampling/015 Borderline SMOTE - Demo.mp4 17.52 MB
05 - Oversampling/016 SVM SMOTE.mp4 82.31 MB
05 - Oversampling/018 SVM SMOTE - Demo.mp4 35.69 MB
05 - Oversampling/019 K-Means SMOTE.mp4 29.82 MB
05 - Oversampling/020 K-Means SMOTE - Demo.mp4 18.58 MB
05 - Oversampling/021 Over-Sampling Method Comparison.mp4 26.92 MB
05 - Oversampling/022 Wrapping up the section.mp4 27.24 MB
05 - Oversampling/023 How to Correctly Set Up a Classifier with Over-sampling.mp4 28.01 MB
05 - Oversampling/024 Setting Up a Classifier - Demo.mp4 16.03 MB
06 - Over and Undersampling/001 Combining Over and Under-sampling - Intro.mp4 30.49 MB
06 - Over and Undersampling/002 Combining Over and Under-sampling - Demo.mp4 26.45 MB
06 - Over and Undersampling/003 Comparison of Over and Under-sampling Methods.mp4 32.08 MB
06 - Over and Undersampling/005 Wrapping up.mp4 7.53 MB
07 - Ensemble Methods/001 Ensemble methods with Imbalanced Data.mp4 13.44 MB
07 - Ensemble Methods/002 Foundations of Ensemble Learning.mp4 9.58 MB
07 - Ensemble Methods/003 Bagging.mp4 8.83 MB
07 - Ensemble Methods/004 Bagging plus Over- or Under-Sampling.mp4 36.96 MB
07 - Ensemble Methods/005 Boosting.mp4 26.8 MB
07 - Ensemble Methods/006 Boosting plus Re-Sampling.mp4 41.63 MB
07 - Ensemble Methods/007 Hybdrid Methods.mp4 11.99 MB
07 - Ensemble Methods/008 Ensemble Methods - Demo.mp4 31.29 MB
07 - Ensemble Methods/009 Wrapping up.mp4 26.11 MB
08 - Cost Sensitive Learning/001 Cost-sensitive Learning - Intro.mp4 15.45 MB
08 - Cost Sensitive Learning/002 Types of Cost.mp4 35.35 MB
08 - Cost Sensitive Learning/003 Obtaining the Cost.mp4 9.22 MB
08 - Cost Sensitive Learning/004 Cost Sensitive Approaches.mp4 5.25 MB
08 - Cost Sensitive Learning/005 Misclassification Cost in Logistic Regression.mp4 9.77 MB
08 - Cost Sensitive Learning/006 Misclassification Cost in Decision Trees.mp4 9.73 MB
08 - Cost Sensitive Learning/007 Cost Sensitive Learning with Scikit-learn.mp4 53.6 MB
08 - Cost Sensitive Learning/008 Find Optimal Cost with hyperparameter tuning.mp4 20.18 MB
08 - Cost Sensitive Learning/009 Bayes Conditional Risk.mp4 42.6 MB
08 - Cost Sensitive Learning/010 MetaCost.mp4 33.98 MB
08 - Cost Sensitive Learning/011 MetaCost - Demo.mp4 17.7 MB
08 - Cost Sensitive Learning/012 Optional MetaCost Base Code.mp4 30.41 MB
09 - Probability Calibration/001 Probability Calibration.mp4 15.19 MB
09 - Probability Calibration/002 Probability Calibration Curves.mp4 13.64 MB
09 - Probability Calibration/003 Probability Calibration Curves - Demo.mp4 61.02 MB
09 - Probability Calibration/004 Brier Score.mp4 7.27 MB
09 - Probability Calibration/005 Brier Score - Demo.mp4 42.81 MB
09 - Probability Calibration/006 Under- and Over-sampling and Cost-sensitive learning on Probability Calibration.mp4 15.8 MB
09 - Probability Calibration/007 Calibrating a Classifier.mp4 21.16 MB
09 - Probability Calibration/008 Calibrating a Classifier - Demo.mp4 44.44 MB
09 - Probability Calibration/009 Calibrating a Classfiier after SMOTE or Under-sampling.mp4 45.79 MB
09 - Probability Calibration/010 Calibrating a Classifier with Cost-sensitive Learning.mp4 21.99 MB
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