Fundamentals of Accelerated Data Science (FADS)

 

Resumen del Curso

Learn how to perform multiple analysis tasks on large datasets using NVIDIA RAPIDS™, a collection of data science libraries that allows end-to-end GPU acceleration for data science workflows.

Prerrequisitos

Experience with Python, ideally including pandas and NumPy.

Suggested resources to satisfy prerequisites: Kaggle's pandas Tutorials, Kaggle's Intro to Machine Learning, Accelerating Data Science Workflows with RAPIDS

Objetivos del curso

  • Implement GPU-accelerated data preparation and feature extraction using cuDF and Apache Arrow data frames
  • Apply a broad spectrum of GPU-accelerated machine learning tasks using XGBoost and a variety of cuML algorithms
  • Execute GPU-accelerated graph analysis with cuGraph, achieving massive-scale analytics in small amounts of time
  • Rapidly achieve massive-scale graph analytics using cuGraph routines

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Entrenamiento en línea

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Instructor-led Online Training:   Este es un curso en línea Guiado por un Instructor

Estados Unidos de América

Entrenamiento en línea 09:00 US/Eastern Inscripción

Canadá

Entrenamiento en línea 09:00 Canada/Eastern Inscripción