Accelerating Feature Engineering with NVIDIA cuDF and cuML
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In this short tutorial, Chris Deotte, Kaggle Grandmaster of NVIDIA, walks you through how GPU-accelerated feature engineering can significantly speed up data processing and improve model performance. You'll learn how to: ✔️ Use NVIDIA cuDF & cuML to accelerate data processing ✔️ Apply cuML target encoding to enhance predictions ✔️ Optimize your XGBoost model for higher AUC scores Join us at NVIDIA GTC for expert talks and hands-on workshops on cutting-edge AI & ML advancements https://nvda.ws/43RFj0C ➡️ Claim a free hands-on Data Science course: https://nvda.ws/4haJYOn ➡️ Join the NVIDIA Developer Program: https://nvda.ws/3OhiXfl ➡️ Enroll in DLI Data Science Learning Path courses https://nvda.ws/3R8lTNA
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