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Plan Szkolenia
Introduction
- Overview of RAPIDS features and components
- GPU computing concepts
Getting Started
- Installing RAPIDS
- cuDF, cUML, and Dask
- Primitives, algorithms, and APIs
Managing and Training Data
- Data preparation and ETL
- Creating a training set using XGBoost
- Testing the training model
- Working with CuPy array
- Using Apache Arrow data frames
Visualizing and Deploying Models
- Graph analysis with cuGraph
- Implementing Multi-GPU with Dask
- Creating an interactive dashboard with cuXfilter
- Inference and prediction examples
Troubleshooting
Summary and Next Steps
Wymagania
- Familiarity with CUDA
- Python programming experience
Audience
- Data scientists
- Developers
14 godzin
Opinie uczestników (5)
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Szkolenie - Scaling Data Analysis with Python and Dask
Trener był bardzo dostępny, aby odpowiedzieć na wszystkie pytania, które zadałem
Caterina - Stamtech
Szkolenie - Developing APIs with Python and FastAPI
Przetłumaczone przez sztuczną inteligencję
Przekazanie wiedzy praktycznej oraz doświadczeń trenera.
Rumel Mateusz - Pojazdy Szynowe PESA Bydgoszcz SA
Zadania do zrealizowania samodzielnie oraz późniejsze wspólne rozwiązywanie
Katarzyna Kopysc-Falenta - CapGemini
Szkolenie - Data Analysis with Python, Pandas, and Numpy
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
