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Course Outline
Introductie
- Overzicht van RAPIDS functies en componenten
- GPU Computerconcepten
Slag
- Installeren RAPIDS
- cuDF, cUML en Dask
- Primitieven, algoritmen en API's
Gegevens beheren en trainen
- Gegevensvoorbereiding en ETL
- Een trainingsset maken met XGBoost
- Testen van het trainingsmodel
- Werken met CuPy array
- Apache Arrow gegevensframes gebruiken
Modellen visualiseren en implementeren
- Grafiekanalyse met cuGraph
- Multi-GPU implementeren met Dask
- Een interactief dashboard maken met cuXfilter
- Voorbeelden van inferentie en voorspelling
Probleemoplossing
Samenvatting en volgende stappen
Requirements
- Bekend met CUDA
- Python programmeerervaring
Publiek
- Datawetenschappers
- Ontwikkelaars
14 Hours
Getuigenissen (5)
Voorbeelden/oefeningen perfect aangepast aan ons domein
Luc - CS Group
Cursus - Scaling Data Analysis with Python and Dask
Machine Translated
De trainer was zeer beschikbaar om alle vragen die ik deed te beantwoorden
Caterina - Stamtech
Cursus - Developing APIs with Python and FastAPI
Machine Translated
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
Cursus - Build REST APIs with Python and Flask
Overdracht van praktische kennis en ervaring van de trainer.
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
Cursus - GUI Programming with Python and PyQt
Machine Translated
As I was the only participant the training could be adapted to my needs.
