MingchaoZhu/InterpretableMLBook resource

Health v2 · maintenance only

Adoption not part of the score

4897 stars · 682 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A Chinese translation of Christoph Molnar's 'Interpretable Machine Learning' book, hosted on GitHub with downloadable releases. It systematically covers interpretable models and model-agnostic explanation methods like feature importance, Shapley values, and LIME.

Use cases

• learn interpretable machine learning in Chinese
• understand how to explain black-box model predictions
• study LIME and Shapley values with theory and examples
• find a systematic reference on model explainability methods
• make machine learning models transparent for regulated domains like finance or healthcare
• prepare to read new interpretability papers on arxiv

When to choose

• you read Chinese and want a free, complete translation of the leading interpretable ML book
• you need both intuitive explanations and mathematical rigor for explainability methods
• you want critical discussion of each method's pros and cons tested on real data

When to avoid

• you need the latest edition updates directly from the author
• you want hands-on Python code exercises, which are only planned as a future addition
• you prefer an English-language resource, in which case use the original book

Facets

learning-resource · maturity maintenance

machine-learning nlp documentation machine-learning tutorials data-science education cross-platform interpretable-ml chinese-translation book explainability shapley-values lime xai

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