Online or onsite, instructor-led live RAPIDS training courses demonstrate through interactive hands-on practice how to use RAPIDS to build GPU-accelerated data pipelines, workflows, and visualizations, applying machine learning algorithms, such as XGBoost, cuML, etc.
RAPIDS training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Stockholm onsite live RAPIDS trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Stockholm, Hötorget
NobleProg classroom in Scandic Klara Hotel Stockholm, Slöjdgatan 7, Stockholm, sweden, 111 57
Near Hötorget and the nearest station is Hötorget. It is right in the heart of shopping street. With 200 meters (5 minutes ...
Near Hötorget and the nearest station is Hötorget. It is right in the heart of shopping street. With 200 meters (5 minutes walk) to the T-Centralen metro station, it is super easy to get around Stockholm, and 800 meters to the Arlanda Express makes it convenient to get to the airport. The location offers a welcoming and professional atmosphere. It is also conveniently close (15 minutes walk) to the Royal Palace for those who want to take in the major sights.
This instructor-led, live training in Stockholm (online or onsite) is aimed at data scientists and developers who wish to use RAPIDS to build GPU-accelerated data pipelines, workflows, and visualizations, applying machine learning algorithms, such as XGBoost, cuML, etc.
By the end of this training, participants will be able to:
Set up the necessary development environment to build data models with NVIDIA RAPIDS.
Understand the features, components, and advantages of RAPIDS.
Leverage GPUs to accelerate end-to-end data and analytics pipelines.
Implement GPU-accelerated data preparation and ETL with cuDF and Apache Arrow.
Learn how to perform machine learning tasks with XGBoost and cuML algorithms.
Build data visualizations and execute graph analysis with cuXfilter and cuGraph.
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