Interpretability

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How to Utilize GNNexplainer for Graph Classification in Torch-Geometric 2.4.0 What will you learn? Learn how to use GNNexplainer for graph classification tasks specifically in the torch-geometric (2.4.0) library. Introduction to the Problem and Solution Graph Neural Networks have revolutionized various domains by efficiently handling structured data like graphs. However, understanding these models is crucial … Read more

LIME Explanation with Watson Assistant in Python

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What will you learn? In this tutorial, you will master the art of explaining machine learning models using LIME (Local Interpretable Model-agnostic Explanations) within a Watson Assistant chatbot environment in Python. By integrating LIME into your chatbot implementation, you will enhance transparency and trust in your conversational AI system. Introduction to the Problem and Solution … Read more