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Deep learning model performance is known for scaling well with data size, but training these models can be notoriously time-consuming. As more companies 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 including TensorFlow, Keras and Pytorch.
  • 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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