Mindful Modeler

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From Theory to Practice: Inductive Biases in Machine Learning
part 1 of the inductive bias series
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Christoph Molnar
A new chapter on generalization
When the pandemic hit, some machine learning research labs dropped their projects to work on COVID-19 classification models, many of them based on X-ray…
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Christoph Molnar
7 perspectives on machine learning
When asked what I work on, I often have to explain what machine learning is. I found myself using different explanations. Beyond explanations for a…
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Christoph Molnar
2
Embrace the clash between domain expertise and machine learning
How to deal with ML model being at odds with domain knowledge
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Christoph Molnar
1

March 2024

How to get from evaluation to final model
We’ve all been there: You’ve set up a machine learning pipeline with tuning, model selection, and evaluation. Tons of data splitting, maybe with…
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Christoph Molnar
4
My perfectly imperfect note-taking system for ML papers
A note-taking system based on Obsidian and Zotero
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Christoph Molnar
3
Machine learning algorithms to live by
The theories you learn shape how you see the world. A lawyer has the legal perspective in mind, an entrepreneur smells business opportunities…
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Christoph Molnar

February 2024

Machine learning never cheats but it may play flawed games
How to become better at designing prediction games
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Christoph Molnar
3
No Free Dessert in Machine Learning
Generalization in machine learning is too narrow. If you want more, you have to give more.
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Christoph Molnar
to kaggle, or not to kaggle
Ultimately, it depends on Bob from IT Services.
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Christoph Molnar
4
Book Launch: ML for Science 🐦‍⬛
A philosophical and pragmatic justification of supervised machine learning in science that you can read for free
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Christoph Molnar
3

January 2024

Machine Learning's Secret Sauce: Competition
What machine learning has to do with marathons, the Fosbury Flop, and running a sub-4-minute mile.
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Christoph Molnar
© 2024 Christoph Molnar
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