Mindful Modeler

6 Things I Hate About SHAP as a Maintainer

A guest post by Tobias Pitters

Sep 24 • 

Christoph Molnar

14

From Frequencies to Coverage: Rethinking What “Representative” Means

From Statistical Distributions to ImageNet’s 1,000 Abaci

Sep 3 • 

Christoph Molnar

11

2

July 2025

Causal Explanations: A Formal Way to Actually Understand Why

A guest post by David A. Kelly, Nathan Blake, and Hana Chockler (King’s College London)

Jul 15 • 

Christoph Molnar

19

Working with Satellite Data? Let’s talk.

I’m writing a hands-on book for ML folks getting into remote sensing.

Jul 4 • 

Christoph Molnar

21

May 2025

Additive Thinking: A Human Habit

A guest post by Vasilis and Julia

May 8 • 

Christoph Molnar

 and 

Vasilis Gkolemis

27

April 2025

Who’s Really Making the Decisions?

LLMs, tariffs, and the silent takeover of decisions

Apr 8 • 

Christoph Molnar

21

SHAP Interpretations Depend on Background Data — Here’s Why

Or why height doesn't matter in the NBA

Apr 1 • 

Christoph Molnar

42

March 2025

The 3rd Edition of Interpretable ML is published 🥳

I published the third edition of the Interpretable Machine Learning book.

Mar 13 • 

Christoph Molnar

28

5

February 2025

Can an office game outperform machine learning?

Wisdom of the crowds, prediction markets, and more fun in the work place.

Feb 25 • 

Christoph Molnar

15

8

How to win an ML competition beyond predictive performance

A dive into the challenges and winning solution

Feb 4 • 

Christoph Molnar

49

January 2025

Why I almost stopped working on Interpretable Machine Learning

7 years ago I started writing the book Interpretable Machine Learning.

Jan 21 • 

Christoph Molnar

31

Seeing the World with a Prediction Mindset

I am fascinated by the topic of prediction.

Jan 14 • 

Christoph Molnar

13

1