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. Onsite live RAPIDS training can be carried out locally on customer premises in Mexico City or in NobleProg corporate training centers in Mexico City.
NobleProg -- Your Local Training Provider
Mexico City - Colonia Del Valle
Av. Insurgentes Sur N° 800 , Mexico City, mexico, 3100
The Colonia Del Valle (HQ) Center is on the eighth floor of an attractive, 20-story steel-gray building on the Avenida de los...
The Colonia Del Valle (HQ) Center is on the eighth floor of an attractive, 20-story steel-gray building on the Avenida de los Insurgentes. The landmark Mexicana de Aviatión Tower is nearby, and the World Trade Center (WTC) is only two blocks away.
Mexico City - Torre Angel
Paseo de la Reforma 350, Mexico City, mexico, 6600
The Mexico City Torre Angel Center is on the 10th and 11th floors of a prestigious curved, reflective high-rise building with...
The Mexico City Torre Angel Center is on the 10th and 11th floors of a prestigious curved, reflective high-rise building with magnificent views to The Angel, the iconic monument to independence on the Paseo de la Reforma.
This instructor-led, live training in Mexico City (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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