mini-pw/2021L-WB-XAI-1
Case Study course for DS studies in Summer 2020/2021
This project offers a structured educational program focused on eXplainable Artificial Intelligence (XAI). It teaches students how to understand and interpret decisions made by machine learning models, covering various explanation methods like LIME and Shapley values. The output is a comprehensive understanding of XAI techniques, applied to practical problems, and communicated through scientific reports and presentations. It's designed for data science students or professionals looking to deepen their knowledge in AI explainability.
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Use this if you are a data science student or professional who needs to learn how to explain complex AI model predictions and communicate those explanations effectively.
Not ideal if you are looking for a ready-to-use software tool or a quick guide on deploying XAI methods without an accompanying structured learning curriculum.
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Jun 26, 2021
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