While Model Trains

Read data blog posts.
Carefully handpicked.
Presented 3 at a time.

Prediction intervals for Random Forests

Ando Saabas

Prediction intervals are commonly used for linear models but are often underused for random forests. Leveraging the fact that a random forest can provide a conditional distribution instead of just the conditional mean makes prediction intervals relatively straightforward to use in this context.

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Writing Robust Tests for Data & Machine Learning Pipelines

Eugene Yan

An in-depth analysis of why certain types of tests break more frequently than others, along with suggestions for creating more robust pipeline tests.

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Mean Squared Terror

Vincent D. Warmerdam

On the risks associated with blindly relying on GridSearch.

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