Large-scale Machine Learning in Spark
Tackle regression problems with the open-source Fregata library
Tuesday, August 29, 2017
Presented by: Andreas Pfadler
Duration: Approximately 60 minutes.
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If you're a data scientist or engineer who needs to perform large-scale machine learning in Spark, you may face these challenges:
TalkingData, China's largest independent Big Data platform, has developed an open-source solution to these challenges — Fregata.
Join Andreas Pfadler, machine learning engineer at TalkingData, for this webcast as he walks through key challenges/solutions to large-scale machine learning and use cases for machine learning at TalkingData. Pfadler will introduce Fregata, a light-weight, large-scale machine learning library on Spark, which aims to tackle large-scale logistic regression and softmax regression problems involving hundreds of millions of training data records.
In this webcast, participants will:
About Andreas Pfadler, Machine Learning Engineer at TalkingData
Andreas Pfadler is a machine learning engineer at Talking Data. He holds a PhD in mathematics and previously worked as a consultant in the financial industry. He is passionate about math, machine learning, software architecture, and cooking. He currently lives in Beijing.