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 trainings in Faro can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Hotel Faro & Beach Club
2, Praça Dom Francisco Gomes 2, 8000-168 Faro, Faro, Portugal, 8000-168 Faro
Situated in the middle of the city center of Faro, Hotel Faro offers stunning views of Ria Formosa and on the historic area, ...
Situated in the middle of the city center of Faro, Hotel Faro offers stunning views of Ria Formosa and on the historic area, being the ideal place for holidays and business. The proximity to Faro International Airport, privileged access to the best beaches in the Algarve and all the services you have in your involvement, make Hotel Faro the perfect choice for your stay. This modern 4-star hotel offers 90 cozy and sophisticated rooms (including 3 suites), a magnificent rooftop with panoramic views of the city where the restaurant are located, the bar and a heated hydrotherapeutic pool. Hotel Faro also offers garage, GYM & Dayspa, 4 multifunctional rooms and a beach club situated on the island of Faro. At the beach season, the offer also includes a daily transfer service to the Beach Club and boating from Ria Formosa, considered one of the 7 wonders of Portugal.
This instructor-led, live training in Faro (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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Testimonials (2)
examples and exercises
Kamil
Course - Introduction to Data Science and AI using Python
Machine Translated
From learning, being able to put the proposed exercises into practice.
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