Mindful Modeler

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Use interpretability to improve and debug your ML model
How I used feature importance to fix my model
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Christoph Molnar
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Don't be dogmatic about interpretability-by-design versus post-hoc
When to use which ML interpretation approach
 • 
Christoph Molnar
4
But have you considered writing your own evaluation metric?
The Strategic Use of Custom Metrics in Machine Learning
 • 
Christoph Molnar
4
Bridging the Gap: From Statistical Distributions to Machine Learning Loss Functions
When I consulted researchers on which statistical analysis to use for their data, a common first step was to think about the distribution of the target…
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Christoph Molnar
5
A Grandmaster's Guide to Machine Learning Challenges
Picking the Right Challenges and Succeeding
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Christoph Molnar
3
Should we stop interpreting ML models because XAI methods are imperfect?
The Case for Imperfect Interpretability
 • 
Christoph Molnar
The Intricate Link Between Compression and Prediction
How Gzip and K-Nearest Neighbors Can Outperform Deep Learning Models
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Christoph Molnar
3
Machine learning eats up science
A new era of science without understanding?
 • 
Christoph Molnar
1
Mindful Modeler
Better machine learning by thinking like a statistician. About model interpretation, paying attention to data, and always staying critical.
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Books By Christoph
Modeling Mindsets
Interpretable Machine Learning
Introduction To Conformal Prediction With Python

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