Mindful Modeler

Home
Archive
About
Machine learning interpretability from first principles
Understand interpretation methods via functional decomposition
 • 
Christoph Molnar
6
New
Top
Community
Imbalanced data? Why "Do Nothing" should be the default
And when “Do Something” is better.”
 • 
Christoph Molnar
1
The SHAP Book is Available in Print 🥳
Interpreting Machine Learning Models With SHAP is now also available as a paperback (in color)! 🎉 You can get it from Amazon. What’s SHAP? SHAP, an…
 • 
Christoph Molnar
Don't "fix" your imbalanced data
Why SMOTE doesn't work for most cases.
 • 
Christoph Molnar
14
Machine learning changed how I see the world
“What do you do for a living?” is often the first question I ask people I meet. For a good reason. What you do for a living often strongly correlates…
 • 
Christoph Molnar
6
How much I've made with Modeling Mindsets
In Germany, it’s a bit of a no-go to talk about money. But I’m often very blunt and ask people anyways what they are making. I’m just too curious. In…
 • 
Christoph Molnar
1
The Art Of Ignoring Career Advice
Embrace advice that resonates; Ignor advice that's misaligned
 • 
Christoph Molnar
4
From bare-bones to holistic machine learning
Machine learning lives on a scale from bare-bones to holistic. Think of bare-bones machine learning as a casting mold to produce puzzle pieces: This…
 • 
Christoph Molnar
Mindful Modeler
Better machine learning by thinking like a statistician. About model interpretation, paying attention to data, and always staying critical.
Recommendations
The Palindrome
The Palindrome
Tivadar Danka
Ahead of AI
Ahead of AI
Sebastian Raschka, PhD
TiddlyWiki Newsletter
TiddlyWiki Newsletter
Jeremy Ruston
Heidi’s Newsletter
Heidi’s Newsletter
Heidi Seibold
Books By Christoph
Modeling Mindsets
Interpretable Machine Learning
Introduction To Conformal Prediction With Python

Mindful Modeler

AboutArchiveRecommendationsSitemap
© 2023 Christoph Molnar
Privacy ∙ Terms ∙ Collection notice
Start WritingGet the app
Substack is the home for great writing