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How do market-leading organizations help data science teams do their best work within the constraints of the enterprise? Data science teams need fast access to business data and a diversity of tools for end-to-end machine learning that can make it challenging for IT to quickly enable them while maintaining data governance and controlling infrastructure costs.

In this webinar, discover how Cloudera Machine Learning (CML), part of the new Cloudera Data Platform (CDP), brings the agility and economics of cloud to self-service data science on governed business data at scale.  

You’ll see how Cloudera Machine Learning lets IT:
  • Easily replicate governed datasets to the public cloud

  • Quickly deploy productivity-boosting ML workspaces for teams

  • Leverage auto-scaling and auto-suspension so teams get the resources they need without runaway costs

And how Data Scientists and Data Engineers will appreciate:
  • Self-service access to data from a browser-based workspace with all the tools needed for end-to-end ML

  • The freedom to experiment and run big jobs with right-sized computing resources including GPUs

  • A consistent user-experience that doesn’t change when the business moves data or infrastructure

The webinar includes a live product demo that will highlight features for IT and end-users.

 

Speakers


Senior Director, ML Products

Matt Brandwein

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Matt Brandwein leads the Machine Learning product group at Cloudera, guiding the next generation platform experience for data scientists and data engineers. Previously he held various product management and product marketing leadership roles at Cloudera. Prior to Cloudera, he built enterprise search and data discovery products at Endeca/Oracle. Matt holds degrees in Computer Science and Mathematics from the University of Massachusetts Amherst.

Field Engineering Lead, Machine Learning

Michael Gregory

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Michael Gregory leads the field team for machine learning at Cloudera helping organizations derive business value from machine learning. Michael has more than 20 years of experience building, selling, implementing, and supporting large-scale data management solutions at Sun Microsystems, Oracle, Teradata, and Hortonworks and has seen and evangelized the power of data to transform organizations and industries from automotive to telco and public sector to manufacturing.

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