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 technologies. 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.
Vartika Singh is a solutions architect at Cloudera with over 12 years of experience applying machine learning techniques to big data problems.
Jeff Shmain is a principal solutions architect at Cloudera. He has 16+ years of financial industry experience with a strong understanding of security trading, risk, and regulations. Over the last few years, Jeff has worked on various use-case implementations at 8 out of 10 of the world’s largest investment banks.
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