Matt Motoki

Matt Motoki

Kaggle Grandmaster (peak world rank #18, $350k+ in prize money). I audit, debug, and improve machine-learning models and forecasts that aren't delivering — especially when you already have data, a model, or a pipeline in place and need to find what's holding it back.

Blog

Seasonal Uniform Average
Seasonal Uniform Average
Handling streaming data with seasonal or cyclic patterns is a common task in data science and machine learning. In this blog post, we discuss a simple implementation of a seasonal uniform average that serves as a solid baseline for forecasting...
Beta Target Encoding
Beta Target Encoding
Bayesian Target Encoding is a feature engineering method that leverages Bayesian principles to convert categorical variables into numeric representations. Beta Target Encoding is a specialized variant designed specifically for binary classification tasks. Beta Target Encoding provides a systematic way to...

Competitions

In my free time, I enjoy doing machine learning competitions. I am a competitions grandmaster on Kaggle.