XAI refers to methods and models that make ML and predictions understandable to humans. This is of importance to various stakeholders and needed to gain trust and adoption of AI models in high-stakes decisions.
Potential Use Cases
Deploying ML in high stakes decisions
Who is This For ?
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PAPER 1. Principles and Practice of Explainable Machine Learning
What are the evaluation criteria for ML explanations?
What are the types of ML explanations?
VIDEO 2. XAI Data Scientist User Journey
How do go about incorporating explainability in the Machine learning development cycle?
What are the Pros. and Cons. of some of the most popular explainability techniques? How do you choose the right explanation?