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[Webinar] Simple Steps to Distributed Deep Learning


In this webinar, Feb 12, find out how distributed deep learning works, get an an overview of the different frameworks, and learn how Databricks is making it easy for data scientists to migrate their single-machine workloads to distributed workloads, at all stages of a deep learning project.



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Hi there,

Deep Learning model performance is known for scaling well with data size, but training these models can be notoriously time-consuming. As more companies (especially major enterprises) adopt deep learning, the need for using distributed deep learning frameworks becomes more important than ever. 

In this webinar, we’ll share:
  • How distributed deep learning works and give you an overview of the different frameworks. 
  • How Databricks is making it easy for data scientists to migrate their single-machine workloads to distributed workloads, at all stages of a deep learning project. 
  • A demo of distributed deep learning training using our newly released feature, HorovodRunner. 

Presented by: 
Yifan Cao, Senior Product Manager, Databricks

Date: Tuesday, February 12, 2019
Time: 10am PT 



Sincerely,
The Databricks Team

Too busy to attend?  Register for the webinar and we will send you a copy of the recording + sample notebooks. 
 
 

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