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. Cancun onsite live RAPIDS trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Cancun, Punta Cancun ICC
Cancun International Convention Center, Blvd. Kukulcan Km. 9, Cancun, mexico, 77500
Work in the heart of "Punta Cancún", the main business area of the city and within the International Convention Center, wher...
Work in the heart of "Punta Cancún", the main business area of the city and within the International Convention Center, where large events and business shows are held.
This modern business center is strategically located in a busy area, surrounded by banks, hotels, restaurants, shops and a wide variety of services.
Fully equipped offices, ready to start working when you enter
Business lounge to work while traveling
Easily booked meeting rooms
Regus IT High Speed Internet Access
Secure parking
Administrative support on request
This instructor-led, live training in Cancun (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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