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- AI
- Data
Explainable AI
Explainable AI is a set of methods and techniques that help make the decision-making processes of machine learning models more transparent and understandable. As AI systems are increasingly used in critical domains like healthcare, finance, and criminal justice, the ability to interpret how these models arrive at their predictions is essential. Explainable AI supports model debugging, regulatory compliance, and stakeholder trust by providing insights into model behavior, feature importance, and potential biases.
Content in this path
Explainable AI
Watch the courses in this path to understand Explainable AI!
- How to understand to Explainable AI
- How to explain Regression Models
- How to explain Classification Models
- How to explain Black Box Models
- How to explain Large Language Models and Agentic AI
- How to explain Ethics and Regulations in Explainable AI
- Learners should have an understanding of machine learning models to get the most out of this course.