Interpretable Machine Learning Applications: Part 2

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Interpretable Machine Learning Applications: Part 2

Coursera · Intermediate ·📐 ML Fundamentals ·1h ago
By the end of this project, you will be able to develop intepretable machine learning applications explaining individual predictions rather than explaining the behavior of the prediction model as a whole. This will be done via the well known Local Interpretable Model-agnostic Explanations (LIME) as a machine learning interpretation and explanation model. In particular, in this project, you will learn how to go beyond the development and use of machine learning (ML) models, such as regression classifiers, in that we add on explainability and interpretation aspects for individual predictions. …
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