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Introduction

RAPIDS for GPU-Accelerated Data Science in Healthcare

Learn how RAPIDS, a new open source project, can speed up your data science workflows by bringing the power of GPU acceleration to your end-to-end machine learning (ML) pipeline.

RAPIDS includes a DataFrame manipulation library (cuDF) for data wrangling and feature engineering that’s very similar to Pandas. It also includes an ML library (cuML) that will provide GPU-accelerated versions of the algorithms available in scikit-learn.

By attending this webinar, you'll learn to use GPU-accelerated ML to:
  • Improve clinical care and operational efficiency;
  • Speed up drug discovery and advance precision medicine; and
  • Derive insight and value from all your data –structured, free text, imaging, and genomics.

WEBINAR REGISTRATION

Tuesday, Dec 4, 2018
11:00am – 12:00pm PT / 20:00 - 21:00 CET
1 Hour

THANK YOU FOR REGISTERING FOR THE WEBINAR

You will receive an email with instructions on how to join the webinar shortly.

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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

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Speaker

Raghav Mani
Developer Relations Manager for Machine Learning in Healthcare, NVIDIA

Raghav Mani manages Developer Relations at NVIDIA, focusing on Machine Learning use cases in Healthcare. Prior to NVIDIA, Raghav worked for 15 years at Epic leading different product & engineering teams. Most recently, he led a team of data scientists and engineers in building Epic’s ML platform on Azure.
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Register

Webinar: Description here

Date & Time: Wednesday, April 22, 2018