Deep Dive into Deep Learning Pipelines continues - Sue Ann Hong & Tim Hunter
844 views · Published 26 October 2017 · 29:48 · Indexed 22 September 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" About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: https://databricks.com/product/unified-data-analytics-platform Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-named-leader-by-gartner
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