Interpretable Machine Learning
Read OriginalThis article provides a hybrid book review and tutorial on Christoph Molnar's 'Interpretable Machine Learning'. It discusses the book's structure, which covers interpretability terminology, interpretable models, and model-agnostic interpretation methods. The second part includes practical Python code examples demonstrating linear and logistic regression as interpretable models, focusing on tabular data and supervised learning.
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