tabular-ml-modeling

Fonctions et usage

State-of-the-art machine learning for large-scale tabular data (millions of rows, thousands of features). Use when building predictive models on tabular/structured data including regression and classification tasks. Covers GPU-accelerated gradient boosting (XGBoost, LightGBM, CatBoost), RAPIDS acceleration (cuDF, cuML), validation strategies, feature engineering, ensembling (hill climbing, stacking), and competition-winning techniques. Includes Numerai-specific optimizations with deep model parameters, era-based validation, multi-target ensembling, and payout scoring. Optimized for NVIDIA A100 GPU with CUDA 12.4.

Démarrage rapide

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.