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On-Demand Webinar

Data Prep for AI: Foundation for Predictive Analytics in Challenging Times

During these critical times, it’s important that the right people collaborate on the right data and get value from AI/ML projects.

The right data is properly cleaned and shaped to deliver insights that can be trusted. In this webinar, you will learn how the latest innovations from Data Prep combined with the DataRobot AI Cloud platform can help teams react fast to changing data, achieve accuracy during uncertainty, and establish trust in your AI/ML initiatives.

We will demonstrate the key cornerstones of enterprise grade data preparation for your AI strategy,  including:

  • Collaborative self-service data preparation to empower novice and expert users to clean and shape raw data into ready data for ML training and deployment
  • Iterative data preparation and model training scaled through cloud native architecture
  • Enterprise governance and data lineage in an age of data and AI democratization

Speakers

Piet Loubser
Piet Loubser

VP Product Marketing - Data Preparation, DataRobot

Mike White
Mike White

Business Analytics Specialist - Data Preparation, DataRobot

  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
    Evariant