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Enterprise data science teams are driving big innovations in machine learning, but this has put them under increased pressure to deliver more models, more frequently, and more rapidly.

In this webinar, Forrester VP & Principal Analyst, Mike Gualtieri, will share data on the top trends in machine learning and lay out what data science teams need to do in order to maximize their output.

Chris Robison, Head of Data Science at Overstock.com, and Craig Kelly, Group Product Manager at Overstock.com, will showcase how they utilized big data and machine learning to

  • Create a one-to-one personalized shopping experience.
  • Decrease cost of moving models to production by nearly 50%.
  • Stand up new models 5x faster than before.

Presenters

Mike Gualtieri

Mike Gualtieri

Forrester VP & Principal Analyst

Mike's research focuses on software technology, platforms, and practices that enable technology professionals to deliver prescient digital experiences and breakthrough operational efficiency. His key technology and platform coverage areas are big data and IoT strategy; Hadoop/Spark; predictive analytics, streaming analytics, and prescriptive analytics; and machine learning, data science, AI, and emerging technologies that make software faster and smarter. Mike is also a leading expert on the intersection of business strategy, architecture, design, and creative collaboration.

Chris Robison

Chris Robison

Head of Marketing Data Science at Overstock.com

Chris is the project lead for Digital Marketing and Fraud Prevention at Overstock. He has extensive experience at early stage startups using Spark and building out Data Science frameworks and solutions. Chris is a graduate of the University of Utah with dual Masters degrees in Computer Science and Statistics.
Craig Kelly

Craig Kelly

Group Product Manager at Overstock.com

Craig leads engineering and data science for the marketing group at Overstock. He is a veteran of multiple startups in the marketing automation space, including most recently at Nanigans, where he led initiatives for programmatic realtime bidding. Craig’s experience and philosophy focuses on driving innovation through scalable, extensible systems heavily leveraged to deliver speed-to-market and velocity of iteration.