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[ DevCourseWeb com ] Udemy - Explainable Artificial Intelligence (XAI) with Python
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01 - Introduction to XAI
001 XAI in Action.mp4
001 XAI in Action_en.srt
002 Need and Importance of XAI.mp4
002 Need and Importance of XAI_en.srt
003 By Design Interpretable Models Decision Tree Glass Box Models.mp4
003 By Design Interpretable Models Decision Tree Glass Box Models_en.srt
004 By Design Interpretable Models Logistic Regression Glass Box Models.mp4
004 By Design Interpretable Models Logistic Regression Glass Box Models_en.srt
005 Black Box Models Part-1.mp4
005 Black Box Models Part-1_en.srt
006 Black Box Models Part-2.mp4
006 Black Box Models Part-2_en.srt
007 XAI Categorization.mp4
007 XAI Categorization_en.srt
02 - Demonstration of By Design Interpretable Models Glass Box
001 Demonstration of Glass Box Models Part-1.mp4
001 Demonstration of Glass Box Models Part-1_en.srt
002 Demonstration of Glass Box Models Part-2.mp4
002 Demonstration of Glass Box Models Part-2_en.srt
003 Need for Train-Test Split.mp4
003 Need for Train-Test Split_en.srt
004 Techniques for Balancing the Dataset.mp4
004 Techniques for Balancing the Dataset_en.srt
005 Code for Balancing the Dataset.mp4
005 Code for Balancing the Dataset_en.srt
006 Quality Metrics for Classification Confusion Matrix, Precision, Recall, F1Score.mp4
006 Quality Metrics for Classification Confusion Matrix, Precision, Recall, F1Score_en.srt
007 Demo of Data Exploration for Stroke Dataset.mp4
007 Demo of Data Exploration for Stroke Dataset_en.srt
008 InterpretML Package.mp4
008 InterpretML Package_en.srt
009 Demo for Logistic Regression Model Explanation.mp4
009 Demo for Logistic Regression Model Explanation_en.srt
010 Demo for Decision Tree Classifier Explanation.mp4
010 Demo for Decision Tree Classifier Explanation_en.srt
011 Explainable Boosting Classifier Working Principle.mp4
011 Explainable Boosting Classifier Working Principle_en.srt
012 Demo for Explainable Boosting Classifier Explanaation.mp4
012 Demo for Explainable Boosting Classifier Explanaation_en.srt
external-assets-links.txt
03 - LIME (Local Interpretable Model Agnostic Explanations)
001 LIME Working Principle.mp4
001 LIME Working Principle_en.srt
002 Mathematical Modelling of LIME Part-1.mp4
002 Mathematical Modelling of LIME Part-1_en.srt
003 Mathematical Modelling of LIME Part-2.mp4
003 Mathematical Modelling of LIME Part-2_en.srt
004 Demo of LIME for tabular Stroke Dataset.mp4
004 Demo of LIME for tabular Stroke Dataset_en.srt
005 LIME Demonstration for textual dataset Part-1.mp4
005 LIME Demonstration for textual dataset Part-1_en.srt
006 LIME Demonstration for textual dataset Part-2.mp4
006 LIME Demonstration for textual dataset Part-2_en.srt
007 LIME Demonstration for textual dataset Part-3.mp4
007 LIME Demonstration for textual dataset Part-3_en.srt
008 Recommended Practice Tasks.html
external-assets-links.txt
04 - SHAP (SHapley Additive exPlanations)
001 SHAP Working Principle.mp4
001 SHAP Working Principle_en.srt
002 Mathematical Modelling of SHAP Part-1.mp4
002 Mathematical Modelling of SHAP Part-1_en.srt
003 Mathematical Modelling of SHAP Part-2.mp4
003 Mathematical Modelling of SHAP Part-2_en.srt
004 Mathematical Modelling of SHAP Part-3.mp4
004 Mathematical Modelling of SHAP Part-3_en.srt
005 SHAP Demonstration.mp4
005 SHAP Demonstration_en.srt
006 Recommended Practice Tasks.html
external-assets-links.txt
05 - Counterfactual Explanations
001 Working Principle of Counterfactual Explanations-1.mp4
001 Working Principle of Counterfactual Explanations-1_en.srt
002 Working Principle of Counterfactual Explanations.mp4
002 Working Principle of Counterfactual Explanations_en.srt
003 Mathematical Modelling of Counterfactual Explanations.mp4
003 Mathematical Modelling of Counterfactual Explanations_en.srt
004 Global Counterfactuals.mp4
004 Global Counterfactuals_en.srt
005 Demo of Counterfactual Explanations on Stroke Dataset.mp4
005 Demo of Counterfactual Explanations on Stroke Dataset_en.srt
006 Recommended Practice Tasks.html
external-assets-links.txt
06 - Google's What-if Tool (WIT) for AI fairness and Counterfactuals
001 Case Study-1 Demo of What-if Tool (WIT).mp4
001 Case Study-1 Demo of What-if Tool (WIT)_en.srt
002 Case Study-2 Demo of What-if Tool (WIT).mp4
002 Case Study-2 Demo of What-if Tool (WIT)_en.srt
003 Case Study-3 Demo of What-if Tool (WIT).mp4
003 Case Study-3 Demo of What-if Tool (WIT)_en.srt
004 Case Study-4 Demo of What-if Tool (WIT).mp4
004 Case Study-4 Demo of What-if Tool (WIT)_en.srt
005 Case Study-5 Demo of What-if Tool (WIT).mp4
005 Case Study-5 Demo of What-if Tool (WIT)_en.srt
external-assets-links.txt
07 - Layer-wise Relevance Propagation (LRP)
001 Interaction Demos of LRP.mp4
001 Interaction Demos of LRP_en.srt
002 Working Principle of LRP.mp4
002 Working Principle of LRP_en.srt
003 Mathematical Modelling of LRP.mp4
003 Mathematical Modelling of LRP_en.srt
004 Demo of LRP on MRI dataset Part-1.mp4
004 Demo of LRP on MRI dataset Part-1_en.srt
005 Demo of LRP on MRI dataset Part-2.mp4
005 Demo of LRP on MRI dataset Part-2_en.srt
006 Recommended Practice Tasks.html
external-assets-links.txt
08 - Contrastive Explanations Method (CEM)
001 Working Principle and Applications of Contrastive Explanations Method (CEM).mp4
001 Working Principle and Applications of Contrastive Explanations Method (CEM)_en.srt
09 - Useful Resources for XAI
001 Useful Resources for XAI.html
11 - Surprise on Completion of Course
001 Open your gift.html
12 - Other resources from the Instructor
001 Other online courses from the Instructor.html
002 Text Books from the Instructor.html
13 - Acknowledgement
001 Gratitude.mp4
001 Gratitude_en.srt
Bonus Resources.txt
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