Traditional approaches to machine learning have stifled developers with a constrained workflow that slows iteration speed and limits model accuracy. For the first time, data scientists now have the tools they need to run the entire data science pipeline, supercharged with GPUs.
In this webinar, we’ll show you how to speed up machine learning with GPU-accelerated XGBoost, for up to 50x faster workflows compared with CPU-only systems.
Join this technical deep dive into GPU-accelerated machine learning, to explore:
- Why XGBoost is currently the most popular and versatile machine learning algorithm
- The benefits of running XGBoost on GPUs vs CPU, and how to get started
- How to effortlessly scale up workflows with greater speed leveraging RAPIDS GPU-accelerated XGBoost, with Pandas-like ease of use
- How to tame terabyte size datasets using multi-GPU, multi-node configurations.