Live Webinar August 29th, 2017 1:00 PM – 2:00 PM EDT
Activity Type: Education – Course or Training  1 Hour  1 PDU free
Provider: O’Reilly

If you’re a data scientist or engineer who needs to perform large-scale machine learning in Spark, you may face these challenges:

  • Tuning Hyperparameters
  • Efficient Parallelization
  • Dealing with large regression models

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.

Andreas 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:

  • Get an overview of common challenges in large-scale machine learning
  • Learn practical methods to address these challenges
  • Get introduced to Fregata, Fregata, a light-weight, large-scale machine learning library developed at Talking Data

Presenter: Andreas Pfadler, (LinkedIn profile) Machine Learning Engineer, TalkingData  holds a PhD in mathematics and previously worked as a consultant in the financial industry. Andreas is passionate about math, machine learning, software architecture, and cooking. He currently lives in Beijing.

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Large-Scale Machine Learning In Spark

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