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Deep Dive into Deep Learning Pipelines continues - Sue Ann Hong & Tim Hunter

844 views · Published 26 October 2017 · 29:48 · Indexed 20 October 2026

Channel: Databricks · 2017 · Science & Technology

"Deep learning has shown tremendous successes, yet it often requires a lot of effort to leverage its power. Existing deep learning frameworks require writing a lot of code to run a model, let alone in a distributed manner. Deep Learning Pipelines is a Spark Package library that makes practical deep learning simple based on the Spark MLlib Pipelines API. Leveraging Spark, Deep Learning Pipelines scales out many compute-intensive deep learning tasks. In this talk we dive into - the various use cases of Deep Learning Pipelines such as prediction at massive scale, transfer learning, and hyperparameter tuning, many of which can be done in just a few lines of code. - how to work with complex data such as images in Spark and Deep Learning Pipelines. - how to deploy deep learning models through familiar Spark APIs such as MLlib and Spark SQL to empower everyone from machine learning practitioners to business analysts. Finally, we discuss integration with popular deep learning frameworks.

Session hashtag: #EUdd3"

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Deep Dive into Deep Learning Pipelines continues - Sue Ann Hong & Tim Hunter

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