While Model Trains

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

Embracing Automated Retraining

Claire Longo & Trevor LaViale

While implementing retraining on a set cadence is easier, dynamic retraining can prevent models from becoming outdated and optimize computational costs.

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Finding bad flamingo drawings with recurrent neural networks

Colin Morris

Using Sketch-RNN as a probability estimator to identify the worst sketches of flamingos in 'Quick, Draw!'.

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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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