Welcome to my collection of Kaggle competition-winning solutions! Here, I showcase my best-performing models and approaches from various Kaggle challenges.
| 🏆 Competition | 📖 Solution | 🚀 Rank |
|---|---|---|
| University of Liverpool - Ion Switching | GitHub Repo | 🥈 32/2618 |
| Novozymes Enzyme Stability Prediction | GitHub Repo | 🥈 47/2482 |
| NFL impact detection | GitHub Repo | 🥈 47/459 |
| SIIM-ISIC Melanoma Classification | GitHub Repo | 🥈 52/3308 |
| CIBMTR - Equity in post-HCT Survival Predictions | GitHub Repo | 🏅 118/3325 |
| M5 Forecasting - Accuracy | GitHub Repo | 🏅 440/5558 |
- 🛠 Models Used: XGBoost, LGBM, Deep Learning (CNN, ViT, etc.)
- 🔍 Key Techniques: Feature engineering, ensembling, augmentation
- 🚀 Optimizations: Hyperparameter tuning, loss functions, efficient inference
Check out my other AI & ML projects in my GitHub profile!
🚀 Always pushing boundaries in AI & ML!