[s5e6] Keep It One Hundred Apr 2026

Leveraging RAPIDS cuDF for lightning-fast GPU data processing.

I’m currently diving into the latest ! The challenge is all about refining models to push the limits of performance. Here’s a breakdown of my current workflow and some key takeaways: 🛠️ The Tech Stack Models: Testing a blend of XGBoost, LightGBM, and CatBoost. [S5E6] Keep it One Hundred

Stick to a 5-fold or 10-fold Stratified CV to ensure the model isn't just chasing noise. Here’s a breakdown of my current workflow and

If you need help with a for feature engineering It’s all about those marginal gains and robust validation

The target is a top 5% finish! It’s all about those marginal gains and robust validation.

Creating interaction terms between the top 3 features yielded a +0.002 boost in CV score.

As noted by top competitors like Chris Deotte , retraining the final ensemble on the full dataset with a fixed iteration count (avg early stopping + 25%) is proving crucial for the leaderboard.