Accelerated Machine Learning with XGBoost on NVIDIA GPUs | Accelerated Data Science Series

Learn how to get a 25x performance increase of XGBoost training, inference, and feature engineering with pandas—all accelerated with RAPIDS running in Google Colab. In this demo, GPUs are used to accelerate workflows using real-world taxi fare data, build baseline models, and incrementally improve model accuracy with advanced feature engineering. All of this is done directly in Google Colab, where RAPIDS and XGBoost are pre-installed for seamless access. 📗 Try this yourself on Google Colab: https://colab.research.google.com/gis... ➡️ Join the NVIDIA Developer Program: https://nvda.ws/3OhiXfl ➡️ Read and subscribe to the NVIDIA Technical Blog: https://nvda.ws/3XHae9F #nvidia #rapidsai #xgboost #machinelearning #datascience 00:00 - Introduction 0:50 – Enable GPU in Google Colab 6:10 – Build baseline model 10:05 – Build XGBoost model 16:11 – RAPIDS On/Off 19:46 – Conclusion