[s5e6] Keep | It One Hundred

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

Below is a structured social media or community post (ideal for LinkedIn, X/Twitter, or Kaggle Discussions) to share your progress or insights. 🚀 Leveling Up: Kaggle S5E6 "Keep it One Hundred" [S5E6] Keep it One Hundred

The provided phrase "[S5E6] Keep it One Hundred" likely refers to the competition, which focuses on a machine learning task related to the "Keep it One Hundred" theme (often involving achieving high accuracy or working with a specific dataset). Creating interaction terms between the top 3 features

Using Optuna for automated hyperparameter tuning. 💡 Key Insights So Far Using Optuna for automated hyperparameter tuning

Leveraging RAPIDS cuDF for lightning-fast GPU data processing.

Stick to a 5-fold or 10-fold Stratified CV to ensure the model isn't just chasing noise.

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.