Все публикации

Analytics within FAME

Analytics within FAME (WP5)

FAME Webinar Series:

FAME Webinar Series: Unlocking the Mystery of Business Processes with AI-Empowered SAX

FAME Webinar Series:

FAME Webinar Series: Strategies for Pricing Data Assets in the Era of AI

6.2 Challenges and

6.2 Challenges and limitations of explainability

5.2 Case studies

5.2 Case studies and real-world applications

6.1 Implementing explainability

6.1 Implementing explainability in AI models

5.1 Comparing and

5.1 Comparing and selecting explainability metrics

4.2 Certainty-Factor based

4.2 Certainty-Factor based explainability

4.3 Fuzzy Logic-based

4.3 Fuzzy Logic-based explainability

3.3 SHAP (SHapley

3.3 SHAP (SHapley Additive exPlanations)

4.1 Overview of

4.1 Overview of rule-based explainability metrics

3.1 Introduction to

3.1 Introduction to model-agnostic explainability techniques

3.2 LIME (Local

3.2 LIME (Local Interpretable Model-agnostic Explanations)

2.3 Interpreting model

2.3 Interpreting model predictions and decisions

2.2 Evaluating fairness

2.2 Evaluating fairness and bias in AI models

2.1 Different types

2.1 Different types of explainability metrics

1.3 Ethical considerations

1.3 Ethical considerations in Explainable AI

1.2 Importance of

1.2 Importance of explainability in AI models

1.1 Overview of

1.1 Overview of Explainable Artificial Intelligence

FAME Webinar Series:

FAME Webinar Series: StreamStory Where Time Series Meet Explainable AI - Visual Journey Through Data

2.1 Overview of

2.1 Overview of Open Banking Regulations

2.3 Compliance and

2.3 Compliance and Data Privacy

4.1 Parties Involved:

4.1 Parties Involved: Banks, FinTechs, and Third-Party Providers

5.1 Emerging Technologies

5.1 Emerging Technologies and Trends