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Course Outline
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
Requirements
- Familiarity with CUDA
- Python programming experience
Audience
- Data scientists
- Developers
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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