2.3 interpreting model predictions and decisions
Published 4 hours ago • No plays • Length 4:03Download video MP4
Download video MP3
Similar videos
-
4:45
2.2 evaluating fairness and bias in ai models
-
15:06
sigmoid tech talk | episode 1 | interpreting model predictions using shap
-
4:10
2.1 different types of explainability metrics
-
3:38
3.2 lime (local interpretable model-agnostic explanations)
-
4:03
6.1 implementing explainability in ai models
-
4:08
1.2 importance of explainability in ai models
-
4:20
6.2 challenges and limitations of explainability
-
18:05
predictive analytics guide for excel data analysts
-
27:37
predictive analysis using python | learn to build predictive models | python training | edureka
-
1:17:04
introduction to conformal prediction and distribution-free uncertainty quantification
-
3:55
3.1 introduction to model-agnostic explainability techniques
-
4:30
5.1 comparing and selecting explainability metrics
-
4:08
4.2 certainty-factor based explainability
-
3:03
what is predictive modeling and how does it work?
-
19:08
predictive models
-
4:00
4.1 overview of rule-based explainability metrics
-
4:10
4.3 fuzzy logic-based explainability
-
5:06
3.3 shap (shapley additive explanations)
-
31:57
predictability and prediction in the specs project -- francisco doblas-reyes
-
5:08
1.3 ethical considerations in explainable ai