Unraveling data with Spark using deep learning and other algorithms from machine learning
Vartika Singh and Jeffrey Shmain walk you through various approaches using the machine learning algorithms available in Spark ML to understand and decipher meaningful patterns in real-world data. Vartika and Jeff also demonstrate how to leverage open source deep learning frameworks to run classification problems on image and text datasets leveraging Spark.
Talk Title | Unraveling data with Spark using deep learning and other algorithms from machine learning |
Speakers | Vartika Singh (Cloudera), Jeffrey Shmain (Cloudera) |
Conference | Strata Data Conference |
Conf Tag | Make Data Work |
Location | New York, New York |
Date | September 26-28, 2017 |
URL | Talk Page |
Slides | Talk Slides |
Video | |
Data analysis has come a long way in terms of dealing with both the size and the complexity of the data itself. Vartika Singh and Jeffrey Shmain walk you through various approaches to unraveling the underlying patterns in the data leveraging Spark, machine learning, and related Along the way, Vartika and Jeff discuss common issues encountered as the data and model sizes grow and demonstrate how to solve analytical problems using deep learning frameworks Caffe and TensorFlow on a Spark cluster. Topics include: