Machine Learning with RAPIDS - Accelerating Data Science Workflows

Explore the origins and capabilities of RAPIDS in this 26-minute conference talk from the NVIDIA AI Tech Workshop at NeurIPS Expo 2018. Learn how RAPIDS accelerates the entire data science pipeline, including data loading, ETL, model training, and inference, to enhance productivity and enable interactive, exploratory workflows. Discover key components such as Apache Arrow, GPU Data Science, and the NVIDIA DGX2 system. Delve into machine learning techniques, dimensionality reduction, graph analytics, and the DataFrame library. Gain insights into KuDF architecture, pickle architecture, string performance, and data importing. Understand how RAPIDS integrates with deep learning frameworks to revolutionize AI infrastructure and data science processes.

Introduction
Apache Arrow
RAPIDS
GPU Data Science
Getting Started
Machine Learning
NVIDIA DGX2
NVIDIA Kmeans
Dimensionality Reduction
Graph Analytics
DataFrame Library
Data Science Infographic
KuDF
KuDF Architecture
Pickle Architecture
Strings
String Performance
Importing Data
Deep Learning Integration